Learning User Interface

ABSTRACT

Provided herein are method, apparatus, and computer program products for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The interface may be facilitated by receiving, by a processor, a selection indication associated with one item of the plurality of dynamic icons. The interface may be facilitated by determining, via the processor, at least one suggested item of the plurality of items based on the selection indication. The interface may also be facilitated by determining a visual bias for at least one suggested dynamic icon representing the at least one suggested item relative to at least one secondary dynamic icon and may be facilitated by applying the visual bias, via the interface, to the at least one suggested dynamic icon.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/230,980, filed Mar. 31, 2014, and entitled “LEARNING USER INTERFACE”,which application claims priority under 35 U.S.C. §119 to U.S.Provisional Application No. 61/932,046, which is entitled “Living UserInterface” and was filed Jan. 27, 2014, each of which is incorporated byreference herein in their entireties.

BACKGROUND OF THE INVENTION

Providers may typically offer goods and/or services (i.e., items) toconsumers and may effect transactions with such consumers via a point ofsale (“POS”) interface, terminal, or system. Applicant has identified anumber of deficiencies and problems associated with conventional POSinterfaces and other associated systems. Through applied effort,ingenuity, and innovation, many of these identified problems have beensolved by developing solutions that are included in embodiments of thepresent invention, many examples of which are described in detailherein.

BRIEF SUMMARY

In general, embodiments of the present invention provided herein includemethods, apparatus, and computer program products for facilitating alearning user interface.

In some example embodiments, a method may be provided that may includepresenting, via an interface, a plurality of dynamic icons representinga plurality of items. Some embodiments of the method may includereceiving, by a processor, a selection indication associated with oneitem of the plurality of dynamic icons. The method may includedetermining, via the processor, at least one suggested item of theplurality of items based on the selection indication. Additionally oralternatively, the method may include determining a visual bias for atleast one suggested dynamic icon representing the at least one suggesteditem relative to at least one secondary dynamic icon, and may includeapplying the visual bias, via the interface, to the at least onesuggested dynamic icon.

In some embodiments, applying the visual bias to the at least onesuggested dynamic icon includes varying a common feature shared betweenthe at least one suggested dynamic icon and the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a size of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a color of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a shading of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a border of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon.

In some embodiments, the visual bias may be temporary. Some embodimentsinclude removing the visual bias after a subsequent selectionindication.

In some embodiments, determining the visual bias may include determininga relevancy score for each of the plurality of items, and may includedetermining the visual bias for the at least one suggested dynamic iconbased on the relevancy score for each for the plurality of items. Therelevancy score for each of the plurality of items may be based onenvironmental data. The environmental data may include at least one of atime of day, time of year, weather, and location. In some embodiments, asuggested relevancy score for each of the at least one suggested itemsis greater than a secondary relevancy score for each of the at least onesecondary items. In some embodiments, a suggested relevancy score foreach of the at least one suggested items is greater than a predeterminedthreshold.

Some embodiments may include determining a second visual bias for asecond suggested dynamic icon relative to the at least one secondarydynamic icon, and may include applying the second visual bias to thesecond suggested dynamic icon.

In some embodiments, determining the at least one suggested item mayinclude accessing transaction data corresponding to each of theplurality of items, and may include determining the at least onesuggested item based on the transaction data. In some embodiments,determining the at least one suggested item may include accessing aselection rate for each item of the plurality of items. The selectionrate may include a rate at which each item of the plurality of items isselected in a same transaction as the one item. The at least onesuggested item may be determined based on the selection rate for eachitem of the plurality of items.

In some embodiments, determining the at least one suggested item mayinclude accessing a sequential selection rate for each item of theplurality of items. The sequential selection rate may include a rate atwhich each item of the plurality of items is selected following aselection of the one item. The at least one suggested item may bedetermined based on the sequential selection rate for each item of theplurality of items. In some embodiments, the at least one suggested itemmay include a first suggested item and a second suggested item, suchthat a first visual bias may be applied to a first dynamic iconrepresenting the first suggested item and a second visual bias may beapplied to a second dynamic icon representing the second suggested itembased on the transaction data for each of the plurality of items.

In some alternative embodiments, an apparatus may be provided that mayinclude at least a processor, and may include a memory associated withthe processor having computer coded instructions therein. The computerinstructions may be configured to, when executed by the processor, causethe apparatus to present, via an interface, a plurality of dynamic iconsrepresenting a plurality of items. Some embodiments of the apparatus maybe configured to receive, by a processor, a selection indicationassociated with one item of the plurality of dynamic icons. Theapparatus may be configured to determine, via the processor, at leastone suggested item of the plurality of items based on the selectionindication. Additionally or alternatively, the apparatus may beconfigured to determine a visual bias for at least one suggested dynamicicon representing the at least one suggested item relative to at leastone secondary dynamic icon, and may be configured to apply the visualbias, via the interface, to the at least one suggested dynamic icon.

In some embodiments, applying the visual bias to the at least onesuggested dynamic icon includes varying a common feature shared betweenthe at least one suggested dynamic icon and the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a size of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a color of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a shading of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a border of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon.

In some embodiments, the visual bias may be temporary. Some embodimentsof the apparatus may be configured to remove the visual bias after asubsequent selection indication.

In some embodiments, determining the visual bias may include determininga relevancy score for each of the plurality of items, and may includedetermining the visual bias for the at least one suggested dynamic iconbased on the relevancy score for each for the plurality of items. Therelevancy score for each of the plurality of items may be based onenvironmental data. The environmental data may include at least one of atime of day, time of year, weather, and location. In some embodiments, asuggested relevancy score for each of the at least one suggested itemsis greater than a secondary relevancy score for each of the at least onesecondary items. In some embodiments, a suggested relevancy score foreach of the at least one suggested items is greater than a predeterminedthreshold.

Some embodiments of the apparatus may determine a second visual bias fora second suggested dynamic icon relative to the at least one secondarydynamic icon, and may include applying the second visual bias to thesecond suggested dynamic icon.

In some embodiments, determining the at least one suggested item mayinclude accessing transaction data corresponding to each of theplurality of items, and may include determining the at least onesuggested item based on the transaction data. In some embodiments,determining the at least one suggested item may include accessing aselection rate for each item of the plurality of items. The selectionrate may include a rate at which each item of the plurality of items isselected in a same transaction as the one item. The at least onesuggested item may be determined based on the selection rate for eachitem of the plurality of items.

In some embodiments, determining the at least one suggested item mayinclude accessing a sequential selection rate for each item of theplurality of items. The sequential selection rate may include a rate atwhich each item of the plurality of items is selected following aselection of the one item. The at least one suggested item may bedetermined based on the sequential selection rate for each item of theplurality of items. In some embodiments, the at least one suggested itemmay include a first suggested item and a second suggested item, suchthat a first visual bias may be applied to a first dynamic iconrepresenting the first suggested item and a second visual bias may beapplied to a second dynamic icon representing the second suggested itembased on the transaction data for each of the plurality of items.

In some example embodiments, a computer program product may be providedthat may include a non-transitory computer readable medium havingcomputer program instructions stored therein. The instructions whenexecuted by a processor may be provided that may include presenting, viaan interface, a plurality of dynamic icons representing a plurality ofitems. Some embodiments of the computer program product may includereceiving, by a processor, a selection indication associated with oneitem of the plurality of dynamic icons. The computer program product mayinclude determining, via the processor, at least one suggested item ofthe plurality of items based on the selection indication. Additionallyor alternatively, the computer program product may include determining avisual bias for at least one suggested dynamic icon representing the atleast one suggested item relative to at least one secondary dynamicicon, and may include applying the visual bias, via the interface, tothe at least one suggested dynamic icon.

In some embodiments, applying the visual bias to the at least onesuggested dynamic icon includes varying a common feature shared betweenthe at least one suggested dynamic icon and the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a size of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a color of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a shading of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon. In some embodiments, applying the visual bias to the atleast one suggested dynamic icon may include varying a border of the atleast one suggested dynamic icon relative to the at least one secondarydynamic icon.

In some embodiments, the visual bias may be temporary. Some embodimentsof the computer program product may remove the visual bias after asubsequent selection indication.

In some embodiments, determining the visual bias may include determininga relevancy score for each of the plurality of items, and may includedetermining the visual bias for the at least one suggested dynamic iconbased on the relevancy score for each for the plurality of items. Therelevancy score for each of the plurality of items may be based onenvironmental data. The environmental data may include at least one of atime of day, time of year, weather, and location. In some embodiments, asuggested relevancy score for each of the at least one suggested itemsis greater than a secondary relevancy score for each of the at least onesecondary items. In some embodiments, a suggested relevancy score foreach of the at least one suggested items is greater than a predeterminedthreshold.

Some embodiments of the computer program product may determine a secondvisual bias for a second suggested dynamic icon relative to the at leastone secondary dynamic icon, and may apply the second visual bias to thesecond suggested dynamic icon.

In some embodiments, determining the at least one suggested item mayinclude accessing transaction data corresponding to each of theplurality of items, and may include determining the at least onesuggested item based on the transaction data. In some embodiments,determining the at least one suggested item may include accessing aselection rate for each item of the plurality of items. The selectionrate may include a rate at which each item of the plurality of items isselected in a same transaction as the one item. The at least onesuggested item may be determined based on the selection rate for eachitem of the plurality of items.

In some embodiments, determining the at least one suggested item mayinclude accessing a sequential selection rate for each item of theplurality of items. The sequential selection rate may include a rate atwhich each item of the plurality of items is selected following aselection of the one item. The at least one suggested item may bedetermined based on the sequential selection rate for each item of theplurality of items. In some embodiments, the at least one suggested itemmay include a first suggested item and a second suggested item, suchthat a first visual bias may be applied to a first dynamic iconrepresenting the first suggested item and a second visual bias may beapplied to a second dynamic icon representing the second suggested itembased on the transaction data for each of the plurality of items.

BRIEF DESCRIPTION OF THE FIGURES

Reference will now be made to the accompanying drawings, which are notnecessarily drawn to scale, and wherein:

FIG. 1 illustrates an example interface having a plurality of dynamicicons in accordance with some embodiments discussed herein;

FIG. 2 illustrates an example system in accordance with some embodimentsdiscussed herein;

FIG. 3 illustrates a schematic block diagram of circuitry that can beincluded in a computing device, such as a provider device, consumerdevice, promotion and marketing service system and/or provider system,in accordance with some embodiments discussed herein;

FIG. 4 illustrates an example relevance system in accordance with someembodiments discussed herein;

FIG. 5 illustrates an example LUI Database in accordance with someembodiments discussed herein;

FIG. 6 illustrates an example Dynamic Icon Module in accordance withsome embodiments discussed herein;

FIG. 7 illustrates an example interface having a plurality of dynamicicons depicting transaction data over a one month elapsed time period inaccordance with some embodiments discussed herein;

FIG. 8 illustrates the example interface of FIG. 7 having a plurality ofdynamic icons depicting transaction data over a two month elapsed timeperiod in accordance with some embodiments discussed herein;

FIG. 9 illustrates the example interface of FIG. 7 having a plurality ofdynamic icons depicting transaction data over a one year elapsed timeperiod in accordance with some embodiments discussed herein;

FIG. 10a illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 10b illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 11a illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 11b illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 12 illustrates an example interface having a plurality ofcategories and a plurality of items within each category in accordancewith some embodiments discussed herein;

FIG. 13 illustrates an example interface having a secondary layer ofdynamic icons in accordance with some embodiments discussed herein;

FIG. 14 illustrates the example interface of FIG. 13, wherein onedynamic icon is visually biased in accordance with some embodimentsdiscussed herein;

FIG. 15 illustrates the example interface of FIG. 14, wherein anotherdynamic icon is visually biased in accordance with some embodimentsdiscussed herein;

FIG. 16 illustrates an example interface having a secondary layer ofdynamic icons in accordance with some embodiments discussed herein;

FIG. 17 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 18 illustrates an example interface depicting a coffee dynamic iconselected and presented in a present transaction listing column inaccordance with some embodiments discussed herein;

FIG. 19 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 20 illustrates an example interface having two dynamic icons shadedto indicate a predictive sequencing in accordance with some embodimentsdiscussed herein;

FIG. 21 illustrates the example interface of FIG. 20 having a soupdynamic icon selected and indicated in the present transaction listingcolumn in accordance with some embodiments discussed herein;

FIG. 22 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 23 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 24 illustrates an example interface having four dynamic iconsaltered to indicate a predictive sequencing in accordance with someembodiments discussed herein;

FIG. 25 illustrates an example interface having a control panel inaccordance with some embodiments discussed herein;

FIG. 26 illustrates the example interface of FIG. 14, wherein a “ThisWeek” option has been selected in accordance with some embodimentsdiscussed herein;

FIG. 27 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 28 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 29 illustrates the example interface of FIG. 15, wherein a“Revenue” option has been selected in accordance with some embodimentsdiscussed herein;

FIG. 30 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 31 illustrates a flow diagram of an example system in accordancewith some embodiments discussed herein;

FIG. 32 illustrates an example interface having a control panel inaccordance with some embodiments discussed herein;

FIG. 33 illustrates an example interface in accordance with someembodiments discussed herein;

FIG. 34 illustrates the example interface of FIG. 33 having a “9:00 am”filter selected in accordance with some embodiments discussed herein;

FIG. 35 illustrates the example interface of FIG. 33 having a “1:00 pm”filter selected in accordance with some embodiments discussed herein;

FIG. 36 illustrates the example interface of FIG. 33 having a “7:00 pm”filter selected in accordance with some embodiments discussed herein;

FIG. 37 illustrates the example interface of FIG. 36 having a rainfilter selected in accordance with some embodiments discussed herein;

FIG. 38 illustrates an example interface having filter icons inaccordance with some embodiments discussed herein;

FIG. 39 illustrates an example interface presenting a profile identifierassociated with a profile data in accordance with some embodimentsdiscussed herein;

FIG. 40 illustrates an example embodiment of a learning user interfacehaving a profile data submenu displayed in accordance with someembodiments discussed herein;

FIG. 41 illustrates an example interface having dynamic icons withsecondary indicator rings activated and dynamic icons with highlightingpresented in accordance with some embodiments discussed herein;

FIG. 42 illustrates the example interface of FIG. 41, wherein thehighlighting is no longer presented in accordance with some embodimentsdiscussed herein;

FIGS. 43-45 illustrate the example interface of FIG. 42 having thegarden dynamic icon selected and the ring around the garden dynamic iconincrementally filling in accordance with some embodiments discussedherein;

FIG. 46 illustrates the example interface of FIG. 42 having the ringaround the garden dynamic icon filled and highlighting presented inaccordance with some embodiments discussed herein;

FIG. 47 illustrates the example interface of FIG. 46 wherein thehighlighting is no longer presented in accordance with some embodimentsdiscussed herein;

FIG. 48 illustrates an example interface having a secondary indicatorring in accordance with some embodiments discussed herein; and

FIG. 49 illustrates a flow diagram of a first interface and a secondinterface in accordance with some embodiments discussed herein.

DETAILED DESCRIPTION

Some embodiments of the present invention will now be described morefully hereinafter with reference to the accompanying drawings, in whichsome, but not all embodiments of the inventions are shown. Indeed, theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein; rather, theseembodiments are provided so that this disclosure will satisfy applicablelegal requirements. Like numbers refer to like elements throughout.

TERMS

As used herein, the terms “data,” “content,” “information,” and similarterms may be used interchangeably to refer to data capable of beingtransmitted, received, and/or stored in accordance with embodiments ofthe present invention. Thus, use of any such terms should not be takento limit the spirit and scope of embodiments of the present invention.Further, where a computing device is described herein to receive datafrom another computing device, it will be appreciated that the data maybe received directly from the another computing device or may bereceived indirectly via one or more intermediary computing devices, suchas, for example, one or more servers, relays, routers, network accesspoints, base stations, hosts, and/or the like, sometimes referred toherein as a “network.” Similarly, where a computing device is describedherein to send data to another computing device, it will be appreciatedthat the data may be sent directly to the another computing device ormay be sent indirectly via one or more intermediary computing devices,such as, for example, one or more servers, relays, routers, networkaccess points, base stations, hosts, and/or the like.

As used herein, the term “promotion and marketing service” may include aservice that is accessible via one or more computing devices and isoperable to provide example promotion and/or marketing services onbehalf of one or more providers that are offering one or moreinstruments that are redeemable for goods, services, experiences and/orthe like. In some examples, the promotion and marketing service may takethe form of a redemption authority, a payment processor, a rewardsprovider, an entity in a financial network, a promoter, an agent and/orthe like. As such, the service is, in some example embodiments,configured to present one or more promotions via one or moreimpressions, accept payments for promotions from consumers, issueinstruments upon acceptance of an offer, participate in redemption,generate rewards, provide a point of sale device or service, issuepayments to providers and/or or otherwise participate in the exchange ofgoods, services or experiences for currency, value and/or the like.

As used herein, the term “provider” may include, but is not limited to,a merchant, business owner, consigner, shopkeeper, tradesperson, vender,operator, entrepreneur, agent, dealer, organization or the like that isin the business of a providing a good, service or experience to aconsumer, facilitating the provision of a good, service or experience toa consumer and/or otherwise operating in the stream of commerce. Forexample, a provider may be in the form of a running company that sellsattire that is generally used by a person who runs or participates inathletic activities.

As used herein, the term “consumer” may include, but is not limited to,a client, customer, purchaser, shopper, user, or the like, who may be inthe position to or does exchange value for one or more vouchers underthe terms defined by one or promotions. For example, and using theaforementioned running company as the example provider, a consumer maybe an individual who is interested in purchasing running shoes.

As used herein, the term “promotion” may include, but is not limited to,any type of offered, presented or otherwise indicated reward, discount,coupon, credit, deal, incentive, discount, media or the like that isindicative of a provider value or the like that upon purchase oracceptance results in the issuance of an instrument that may be usedtoward at least a portion of the purchase of particular goods, servicesand/or experiences defined by the promotion. An example promotion, usingthe aforementioned running company as the example provider, is $25 for$50 toward running shoes. In some examples, the promotion defines anaccepted value (e.g., a cost to purchase the promotion), a providervalue (e.g., the value of the resultant instrument beyond the acceptedvalue), a residual value (e.g., the value upon return or upon expiry ofone or more redemption parameters), one or more redemptions parametersand/or the like. Using the running company promotion as an example, theaccepted value is $25 and the provider value is $50. In this example,the residual value may be equal to the accepted value.

As used herein, the term “item” refers to any product, good, promotion,service, option, or other tangible or intangible item that may bedisplayed in a user interface.

As used herein, the term “feature” refers to the size, shape, color,text, highlighting, shading, opacity, image overlay, or any otherdiscernible attribute of a tangible or intangible visualization of anitem.

As used herein, the term “item data” refers to any data related to anitem, such as, but not limited to, transaction data, environmental data,item characteristic data, business data, and any other data that mayserve to distinguish one or more items from each other.

As used herein, the term “profile identifier” refers to any data thatidentifies a user, consumer, provider, provider employee, or promotionand marketing service. For example, and without limitation, a profileidentifier may include a unique identifier, an IP address, a MACaddress, a merchant identifier, a customer identifier, and the like.

As used herein, the term “profile data” refers to any data associatedwith a profile identifier, such as, but not limited to, transactiondata, biographical data, preference data, or any other data that mayserve to distinguish one or more profiles from each other.

As used herein, the term “transaction data” refers to any item orprofile data related to the buying, selling, or offering of an item,such as, but not limited to, sales data including historical andpredicted revenue for each item, historical and predicted profits foreach item, quantities sold for each item, quantity of customerspurchasing each item, overall selection rate of each item, popularity ofan item, or a selection rate per transaction or per customer of eachitem. Transaction data may also include redemption data, in the case ofa promotion that must be redeemed, or may include return data for anitem or promotion that is returned. In some embodiments, transactiondata may include a consumer rating of an item. The transaction data mayalso include transactions with respect to profile information, such astransactions involving a single profile or related group of profiles.

As used herein, the term “environmental data” refers to contextual orenvironmental information associated with an item and/or associated withtransactions involving items such as, without limitation, a time of day,time of year, weather, season, geographic or hyper-geographic location,or any other data that gives context to an item and/or to a transaction.

As used herein, the term “business data” refers to commercial orstrategic data associated with an item that may define metrics for aprovider or promotion and marketing service. For example and withoutlimitation, goal data, such as sales goals, impression goals, redemptiongoals, revenue goals, profit goals or inventory data may serve asbusiness data.

As used herein, the term “characteristic information” refers to anyidentifying attributes of an item that may serve to distinguish the itemfrom other items, such as, but not limited to, physical characteristics(e.g. color, texture, flavor, crunchiness, etc.) and/or healthcharacteristics (e.g. vitamin and nutrient content).

As used herein, the term “biographical data” refers to informationassociated with a person(s) (e.g., consumer, provider employee, etc.)identified in a profile, such as, for example, birth dates, allergies,socio-economic data, interests, place of residence, login credentialinformation, and/or any other identifying information about a profile.

As used herein, the term “preference data” refers to one or more optionsassociated with a profile, such that the preference data tracks theprofile holder's interests and selections for various user-selectableinterface options. Preference data may also include, without limitation,location data (e.g., GPS data, operating system location, etc.)associated with activity of a user associated with a profile.

As used herein, the term “dynamic icon” refers to any visualization ofan item, such as, but not limited to, buttons, pictures, photos,symbols, QR codes, ID numbers, or any other visual representation of anitem.

As used herein, the term “visual bias” refers to presenting,emphasizing, altering, or enhancing one or more features of a dynamicicon, via an interface, in order to convey information associated withan item represented by the dynamic icon. A visual bias may change ormodify a common feature shared by one or more dynamic icons. Forexample, a visual bias may be used to indicate a relationship betweentwo or more dynamic icons, such as a relative item or profile databetween the items represented by the two or more dynamic icons. Inanother embodiment, a visual bias may identify a suggested icon asdistinct from one or more secondary icons. A visual bias may also beused to convey objective information about an item represented by thedynamic icon, such as item or profile data. In some embodiments, thevisual bias may be presented as a visual indication.

As used herein, the term “common feature” refers to any feature sharedby two or more dynamic icons. For example, in some embodiments, twodynamic icons may both have the same shape (e.g., circles) representingtwo different items. In some embodiments, the interface may visuallybias one of or both of the dynamic icons by changing the common circularfeature of the dynamic icons, such as by altering the size, color,border, shading, or any other attribute of the common feature toindicate a distinction between the two dynamic icons.

As used herein, the term “visual indication” refers to an altering ofany discernible feature of a dynamic icon, such as by highlighting,shading, flashing, pulsing, sizing, coloring, displaying text,overlaying an image, repositioning, presenting submenus or any visualbiasing that may visually attract a user's attention to a dynamic icon.

Overview

Various embodiments of the invention are directed to a learning userinterface 1 (referred to herein simply as “the interface,” the “learninguser interface,” or the “LUI”), for example, as shown in FIG. 1, that isconfigured to be adaptive, intuitive, and to allow a user (e.g., aconsumer, provider, provider employee, or promotion and marketingservice) to visualize or perceive information (e.g., transaction data,business data, relevancy data, etc.) associated with a set of items. Theinterface 1 may be used as part of a standalone service, application, ordevice or it may be applied as a layer atop an existing serviceapplication or device.

The interface 1 may present one or more dynamic icons to a user. Thedynamic icons may visually represent one or more corresponding items.For example, in some embodiments, the interface 1 may be a point of saleterminal that presents dynamic icons representing items for sale. Theinterface 1 may visually bias the dynamic icons in order to indicate asuggested icon to a user relative to a secondary icon. The suggestedicon may be determined based on item data corresponding to therepresented items and/or profile data corresponding to a profileidentifier. The items may be visually biased in order to make theinterface more intuitive and easier to use by visually emphasizing orbiasing those dynamic icons that are more likely to be selected or ofinterest to a given user.

As will be discussed in greater detail below, the interface 1 is notlimited to displaying data concerning provider items and can instead beconfigured to display a wide variety of data characteristics for any setof data that might be of interest to a user. The interface 1 may be usedto visualize any set of item or profile data for any purpose and it maybe used in connection with numerous exemplary system architectures asexplained in further detail herein.

In some embodiments, the interface 1 may be configured to be used by aprovider, consumer, promotion and marketing service, or a third-partyand may be tailored to suit each party's interests or specific dataneeds. For example, the embodiment shown in FIG. 1 illustrates a pointof sale restaurant interface with menu options as the available items.In some embodiments, the interface 1 may be disposed in electricalcommunication with a point of sale terminal. Electrical communicationmay include, but is not limited to, being displayed on an attachedscreen, being wirelessly transmitted to a remote screen, being presentedto a consumer, provider, or third party screen, or any other means toassociate the interface with the point of sale terminal. In otherembodiments, the interface 1 may be configured as an online shoppinginterface. One of ordinary skill in the art will appreciate that the LUIrelated concepts discussed herein, may be applied to better visualizecharacteristics of interest for a wide variety of item and/or data sets.

Exemplary Architecture

FIG. 2 shows system 200 including an example network architecture for asystem, which may include one or more devices and sub-systems that areconfigured to implement some embodiments discussed herein. For example,system 200 may include provider system 216, which can include, forexample, the circuitry disclosed in FIGS. 3-4, a provider server, orprovider database, among other things (not shown). The provider system216 may include any suitable network server and/or other type ofprocessing device. In some embodiments, the provider system 216 maydetermine and transmit commands and instructions for rendering one ormore visually biased dynamic icons to consumer devices 210A-210N,provider devices 212A-212M, and/or one or more third party systems 218using data from the LUI database 312.

Provider system 216 can communicate with one or more consumer devices210A-210N and/or one or more provider devices 212A-212N via network 214.In this regard, network 214 may include any wired or wirelesscommunication network including, for example, a wired or wireless localarea network (LAN), personal area network (PAN), metropolitan areanetwork (MAN), wide area network (WAN), or the like, as well as anyhardware, software and/or firmware required to implement it (such as,e.g., network routers, etc.). For example, network 214 may include acellular telephone, an 802.11, 802.16, 802.20, and/or WiMax network.Further, the network 214 may include a public network, such as theInternet, a private network, such as an intranet, or combinationsthereof, and may utilize a variety of networking protocols now availableor later developed including, but not limited to TCP/IP based networkingprotocols.

Consumer devices 210A-210N and/or provider devices 212A-812M may each beimplemented as a personal computer and/or other networked device, suchas a cellular phone, tablet computer, mobile device, point of saleterminal, inventory management terminal etc., that may be used for anysuitable purpose in addition to presenting the interface to facilitatebuying items and/or offering items for sale. The depiction in FIG. 2 of“N” consumers and “M” providers is merely for illustration purposes. Inone embodiment, the consumer devices 210A-210N may be configured todisplay an interface on a display of the consumer device for viewing atleast one dynamic icon, which may be provided by the provider system216. According to some embodiments, the provider devices 212A-212M maybe configured to display the interface on a display of the providerdevice for viewing, creating, editing, and/or otherwise interacting witha dynamic icon. In some embodiments, an interface of a consumer device210A-210N may be different from an interface of a provider device212A-212M. The consumer device 210A-210N may be used in addition to orinstead of the provider device 212A-212M. System 200 may also include atleast one promotion and marketing service system 204 and/or 3rd partysystem 218, among other things.

FIG. 3 shows a schematic block diagram of circuitry 300, some or all ofwhich may be included in, for example, provider system 216, promotionand marketing service system 204, consumer devices 210A-210N and/orprovider devices 212A-212M. Any of the aforementioned systems or devicesmay include the circuitry 300 and may be configured to, eitherindependently or jointly with other devices in a network 214 perform thefunctions of the circuitry 300 described herein. As illustrated in FIG.3, in accordance with some example embodiments, circuitry 300 canincludes various means, such as processor 302, memory 304,communications module 306, and/or input/output module 308. In someembodiments, dynamic icon module 310 and/or a relevance system 314 mayalso or instead be included. As referred to herein, “module” includeshardware, software and/or firmware configured to perform one or moreparticular functions. In this regard, the means of circuitry 300 asdescribed herein may be embodied as, for example, circuitry, hardwareelements (e.g., a suitably programmed processor, combinational logiccircuit, and/or the like), a computer program product comprisingcomputer-readable program instructions stored on a non-transitorycomputer-readable medium (e.g., memory 304) that is executable by asuitably configured processing device (e.g., processor 302), or somecombination thereof.

Processor 302 may, for example, be embodied as various means includingone or more microprocessors with accompanying digital signalprocessor(s), one or more processor(s) without an accompanying digitalsignal processor, one or more coprocessors, one or more multi-coreprocessors, one or more controllers, processing circuitry, one or morecomputers, various other processing elements including integratedcircuits such as, for example, an ASIC (application specific integratedcircuit) or FPGA (field programmable gate array), or some combinationthereof. Accordingly, although illustrated in FIG. 3 as a singleprocessor, in some embodiments processor 302 comprises a plurality ofprocessors. The plurality of processors may be embodied on a singlecomputing device or may be distributed across a plurality of computingdevices collectively configured to function as circuitry 300. Theplurality of processors may be in operative communication with eachother and may be collectively configured to perform one or morefunctionalities of circuitry 300 as described herein. In an exampleembodiment, processor 302 is configured to execute instructions storedin memory 304 or otherwise accessible to processor 302. Theseinstructions, when executed by processor 302, may cause circuitry 300 toperform one or more of the functionalities of circuitry 300 as describedherein.

Whether configured by hardware, firmware/software methods, or by acombination thereof, processor 302 may comprise an entity capable ofperforming operations according to embodiments of the present inventionwhile configured accordingly. Thus, for example, when processor 302 isembodied as an ASIC, FPGA or the like, processor 302 may comprisespecifically configured hardware for conducting one or more operationsdescribed herein. Alternatively, as another example, when processor 302is embodied as an executor of instructions, such as may be stored inmemory 304, the instructions may specifically configure processor 302 toperform one or more algorithms and operations described herein, such asthose discussed in connection with FIGS. 1-48.

Memory 304 may comprise, for example, volatile memory, non-volatilememory, or some combination thereof. Although illustrated in FIG. 3 as asingle memory, memory 304 may comprise a plurality of memory components.The plurality of memory components may be embodied on a single computingdevice or distributed across a plurality of computing devices. Invarious embodiments, memory 304 may comprise, for example, a hard disk,random access memory, cache memory, flash memory, a compact disc readonly memory (CD-ROM), digital versatile disc read only memory (DVD-ROM),an optical disc, circuitry configured to store information, or somecombination thereof. Memory 304 may be configured to store information,data (including item data and/or profile data), applications,instructions, or the like for enabling circuitry 300 to carry outvarious functions in accordance with example embodiments of the presentinvention. For example, in at least some embodiments, memory 304 isconfigured to buffer input data for processing by processor 302.Additionally or alternatively, in at least some embodiments, memory 304is configured to store program instructions for execution by processor302. Memory 304 may store information in the form of static and/ordynamic information. This stored information may be stored and/or usedby circuitry 300 during the course of performing its functionalities.

Communications module 306 may be embodied as any device or meansembodied in circuitry, hardware, a computer program product comprisingcomputer readable program instructions stored on a computer readablemedium (e.g., memory 304) and executed by a processing device (e.g.,processor 302), or a combination thereof that is configured to receiveand/or transmit data from/to another device and/or network, such as, forexample, a second circuitry 300 and/or the like. In some embodiments,communications module 306 (like other components discussed herein) canbe at least partially embodied as or otherwise controlled by processor302. In this regard, communications module 306 may be in communicationwith processor 302, such as via a bus. Communications module 306 mayinclude, for example, an antenna, a transmitter, a receiver, atransceiver, network interface card and/or supporting hardware and/orfirmware/software for enabling communications with another computingdevice. Communications module 306 may be configured to receive and/ortransmit any data that may be stored by memory 304 using any protocolthat may be used for communications between computing devices.Communications module 306 may additionally or alternatively be incommunication with the memory 304, input/output module 308 and/or anyother component of circuitry 300, such as via a bus.

Input/output module 308 may be in communication with processor 302 toreceive an indication of a user input and/or to provide an audible,visual, mechanical, or other output to a user (e.g., provider and/orconsumer). Some example visual outputs that may be provided to a user bycircuitry 300 are discussed in connection with FIGS. 1-48. As such,input/output module 308 may include support, for example, for akeyboard, a mouse, a joystick, a display, a touch screen display, amicrophone, a speaker, a RFID reader, barcode reader, biometric scanner,and/or other input/output mechanisms. In embodiments wherein circuitry300 is embodied as a server or database, aspects of input/output module308 may be reduced as compared to embodiments where circuitry 300 isimplemented as an end-user machine (e.g., consumer device and/orprovider device) or other type of device designed for complex userinteractions. In some embodiments (like other components discussedherein), input/output module 308 may even be eliminated from circuitry300. Alternatively, such as in embodiments wherein circuitry 300 isembodied as a server or database, at least some aspects of input/outputmodule 308 may be embodied on an apparatus used by a user that is incommunication with circuitry 300. Input/output module 308 may be incommunication with the memory 304, communications module 306, and/or anyother component(s), such as via a bus. One or more than one input/outputmodule and/or other component can be included in circuitry 300.

Dynamic icon module 310 and relevance system 314 may also or instead beincluded and configured to perform the functionality discussed hereinrelated to generating, ranking, arranging, presenting, and/or editingitem data and/or profile data. In some embodiments, some or all of thefunctionality of generating, ranking, arranging, presenting, and/orediting item data and/or profile data may be performed by processor 302.In this regard, the example processes and algorithms discussed hereincan be performed by at least one processor 302, dynamic icon module 310,and/or relevance system 314. For example, non-transitory computerreadable media can be configured to store firmware, one or moreapplication programs, and/or other software, which include instructionsand other computer-readable program code portions that can be executedto control each processor (e.g., processor 302, dynamic icon module 310,and/or relevance system 314) of the components of system 300 toimplement various operations, including the examples shown above. Assuch, a series of computer-readable program code portions are embodiedin one or more computer program goods and can be used, with a computingdevice, server, and/or other programmable apparatus, to producemachine-implemented processes.

In some embodiments, a LUI database 312, 430, 500 may be provided thatincludes item data, profile data, and/or analytical engine data. Asshown in FIG. 5, item data 515 may include transaction data 535,environmental data 540, business data 545, and/or characteristic data.Profile data 510, in some embodiments, may include transaction data 520,biographical data 525, and/or preference data 530. Additionally oralternatively, the LUI database 312, 430, 500 may include analyticalengine data 505, which provides any additional information needed by therelevance system 314, 400 and/or dynamic icon module 310, 600 incomputing visual bias of the dynamic icons.

For example, returning to FIG. 3, dynamic icon module 310 can beconfigured to analyze multiple sets of item data and/or profile data(e.g., including various combinations of environmental, business,biographical, transactional data, etc.), such as the data in the LUIdatabase 312, in view of consumer, provider, and/or promotion andmarketing service needs (such as, e.g., preferences for certain items,popularity of certain items, excess inventory sales goals, and/orinventory service life information) to present one or more of visuallybiased dynamic icons representing items to present on a provider deviceand/or a consumer device. In this way, dynamic icon module 310 maysupport multiple algorithms, including those discussed below withrespect to transaction data, environmental data, predictive sequencing,various filters, etc. Further, the present configuration can enableflexibility in terms of configuring additional contexts.

In some embodiments, with reference to FIG. 6, the dynamic icon module310, 600 may include a dynamic icon generation module 605, a visual biasdetermining module 610, and/or a dynamic icon rendering module 615. Thedynamic icon generating module may receive one or more items offered bya provider and/or a promotion and marketing service and may generatedynamic icons for each item. The dynamic icons may be generated based ona set of predetermined templates, may be based on a particular user orset of user preferences, and/or may be determined based on the itemsthemselves (e.g., shaped to approximate the shape of an associated item,etc.).

During or after the generation of the dynamic icons, the dynamic iconmodule 310, 600 may determine a visual bias using the visual biasdetermining module 610. The visual bias determining module may use anyof the algorithms or processes disclosed herein for determining a visualbias. For example, the visual bias module may compare various data fromthe LUI database 312, 430, 500, such as, but not limited to, transactiondata, environmental data, business data, relevancy scores, and/orbiographical data.

In some embodiments, the dynamic icon module 310, 600 may include adynamic icon rendering module 615. In some other embodiments, such aswhen the circuitry 300 is embodied in a provider system 216 or promotionand marketing service system 204, the dynamic icon rendering module 615may be located in another circuitry 300 or another device, such as theconsumer devices 210A-210N or provider devices 212A-212M.

The dynamic icon module 310 can be configured to access datacorresponding to multiple items, and generate an initial visual bias forthe multiple items and/or an initial ranking of the multiple items. Insome embodiments, the multiple items can be ranked in accordance with atransaction data, wherein multiple items are ranked based on factorssuch as selection rate, usage rate, popularity, profit, etc. Thereafter,the dynamic icon module 310 can adjust the initial visual biasing forthe multiple items and/or the ranking of the multiple items at variousperiods or refresh rates. Dynamic icon module 310 may adjust the visualbias and/or the rankings of the items in one or multiple ways. Forexample, the dynamic icon module 310 may update the initial visual biasor subsequent visual bias for the multiple items and/or the initialranking of the multiple items or subsequent ranking(s) of the multipleitems. As another example, the dynamic icon module 310 may use one ormore rules to adjust the initial visual bias, the subsequent visualbias, the initial ranking of the multiple items, or the subsequentranking(s) of the multiple items (such as by excluding or diminishing(i.e., visually de-emphasizing) an item based on a business rule).

Alternatively and/or additionally, the dynamic icon module 310 mayconsider any information or data in visually biasing the dynamic icons.In some embodiments, the dynamic icons are visually biased on anabsolute scale, such that the visual bias is related only to anindividual item (e.g., sales or transaction data for a particular item)and not related or ranked according to the other items. In someembodiments, the dynamic icon module 310 visually biases the dynamicicons, as described above, in order to convey one or more suggesteddynamic icons. The suggested dynamic icons may be determinedautomatically by the dynamic icon module 310 or may be chosen based onthe user preference data.

In some embodiments, as detailed herein, the dynamic icon module 310 mayvisually bias the dynamic icons based on one or more relevancy scoresfor the items. Additionally or alternatively to the dynamic icon module310, the circuitry 300 may include a relevance system 314, 400, whichcalculates relevancy scores for a plurality of items. The relevancesystem 314, 400 may be included in any one or more of the providersystem 216, the promotion and marketing service system 204, the 3^(rd)party system 218, the consumer devices 210A-210N, and/or the providerdevices 212A-212M. The relevance system 314, 400 may also interact withother systems and servers over the network 214 that contain data, whichmay be used to calculate relevancy. Additionally, in some embodiments,the relevance system 314, 400 may be located in a provider system 216and/or promotion and marketing service system 204 and interact withremote devices, such as consumer 210A-210N or provider 212A-212N devicesto facilitate visual biasing.

With reference to FIG. 4, whether used locally or over a network, therelevance system 314, 400 may be used to calculate the relevancy scoresfor the items used in the interface. The system may receive a pluralityof inputs 405, 410 from the circuitry 300 and process the inputs withinthe relevance system to produce a relevance output 435, which mayinclude a relevancy score. In some embodiments, the relevance system314, 400 may execute context determination 415, process the data in ananalytical engine 420, and output the results via a communicationsinterface 425. Each of these steps may pull data from a plurality ofsources including the LUI Database 430.

When inputs 405, 410 are received by the relevance system 314, 400, acontext determination 415 may first be made. A context determinationincludes such information as a user preference data, what item or userare the items being compared to for the relevancy scoring, and underwhat circumstances has the interface or system has requested therelevancy information. These inputs may give context to the relevancesystem's 314, 400 analysis to determine to what reference source therelevancy score is based. For example, the context determination module415 may instruct the relevance system to calculate relevancy scoresbased on a specific user. In some embodiments, the context determinationmodule 415 may instruct the relevance system to calculate relevancyscores for the items based on item data for a specific location. Thecontext determination module 415 may select any criteria based on anynumber of preferences and automatic determinations around which tocalculate the relevancy scores.

The relevance system 314, 400 may then compute the relevancy scoresusing the analytical engine 420. The analytical engine 420 drawsinformation about the profile and the items from the LUI database 312,430, 500 and then, in light of the context determination module's 415determination, computes a relevancy score for each of the items. Theanalytical engine 420, in some embodiments, may produce a hierarchy ofrelevancy scores for the items based on the similarities between a givenitem, or profile data, and each of the plurality of items. Theanalytical engine 420 may compare each item with the desired context 415to determine the relevancy scores. The communications interface 425 thenoutputs 435 the relevancy scores to the dynamic icon module 310 on alocal or remote circuitry 300 for visual biasing.

Additional descriptions of relevance determination algorithms foridentifying promotions relevant to a consumer or other profile data thatmay be used alternatively or additionally are described in U.S. patentapplication Ser. No. 13/411,502, filed Mar. 2, 2012, titled “RELEVANCESYSTEM FOR CONSUMER DEALS”, U.S. patent application Ser. No. 13/829,581entitled “PROMOTION OFFERING SYSTEM” filed on Mar. 14, 2013, and U.S.patent application Ser. No. 12/776,028, now U.S. Pat. No. 8,355,948,titled “SYSTEM AND METHODS FOR DISCOUNT RETAILING” filed on May 7, 2010,the entirety of each is incorporated by reference herein.

In some embodiments, a consumer device 210A-210N or a provider device212A-212N may receive or access the profile identifier. The profileidentifier may be received remotely, via wireless communication ortethered communication, or directly, via input into one of the devices210A-210N, 212A-212N. For example, in some embodiments, the consumer mayhave a remote device, such as a mobile device or key fob that interactswith the devices 210A-210N, 212A-212N to transmit a profile identifierand other related profile data. In another example, a consumer maysimply provide login credentials through the interface of their consumerdevice. The devices 210A-210N, 212A-212N may receive the profileidentifier and transfer it to the circuitry 300. The circuitry 300 maythen access the LUI database 312 to retrieve profile data 510 associatedwith the profile identifier and transfer the profile identifier and/orthe profile data to the relevance system 314, 400 and/or the dynamicicon module 310, 600.

In some embodiments, the system 200 may be configured to present via theinterface one or more visually biased dynamic icons by interacting withone or more circuitries 300 over a network 214. In some embodiments, thecircuitry 300 may be a local circuit configured to visually bias thedynamic icons based on a local LUI database 312. In some embodiments,multiple devices 210A-210N, 212A-212N may present interfaces todifferent users and may bias a plurality of dynamic icons differentlybased on the particular user. The interfaces may be used in a singleprovider location, multiple provider locations, in the locations ofmultiple providers, and/or in any promotion and marketing servicelocations.

As will be appreciated, any such computer program instructions and/orother type of code may be loaded onto a computer, processor or otherprogrammable apparatus's circuitry to produce a machine, such that thecomputer, processor other programmable circuitry that execute the codeon the machine create the means for implementing various functions,including those described herein.

It is also noted that all or some of the information presented by theexample displays discussed herein can be based on data that is received,generated and/or maintained by one or more components of a local ornetworked system and/or circuitry 200, 300. In some embodiments, one ormore external systems (such as a remote cloud computing and/or datastorage system) may also be leveraged to provide at least some of thefunctionality discussed herein.

As described above and as will be appreciated based on this disclosure,embodiments of the present invention may be configured as methods,personal computers, servers, mobile devices, backend network devices,and the like. Accordingly, embodiments may comprise various meansincluding entirely of hardware or any combination of software andhardware. Furthermore, embodiments may take the form of a computerprogram product on at least one non-transitory computer-readable storagemedium having computer-readable program instructions (e.g., computersoftware) embodied in the storage medium. Any suitable computer-readablestorage medium may be utilized including non-transitory hard disks,CD-ROMs, flash memory, optical storage devices, or magnetic storagedevices.

Embodiments of the present invention have been described above withreference to block diagrams and flowchart illustrations of methods,apparatuses, systems and computer program goods. It will be understoodthat each block of the circuit diagrams and process flowcharts, andcombinations of blocks in the circuit diagrams and process flowcharts,respectively, can be implemented by various means including computerprogram instructions. These computer program instructions may be loadedonto a general purpose computer, special purpose computer, or otherprogrammable data processing apparatus, such as processor 302, dynamicicon module 310, and/or relevance system 314 discussed above withreference to FIG. 3, to produce a machine, such that the computerprogram product includes the instructions which execute on the computeror other programmable data processing apparatus create a means forimplementing the functions specified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable storage device (e.g., memory 304) that can direct acomputer or other programmable data processing apparatus to function ina particular manner, such that the instructions stored in thecomputer-readable storage device produce an article of manufactureincluding computer-readable instructions for implementing the functiondiscussed herein. The computer program instructions may also be loadedonto a computer or other programmable data processing apparatus to causea series of operational steps to be performed on the computer or otherprogrammable apparatus to produce a computer-implemented process suchthat the instructions that execute on the computer or other programmableapparatus provide steps for implementing the functions discussed herein.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of means for performing the specified functions,combinations of steps for performing the specified functions and programinstruction means for performing the specified functions. It will alsobe understood that each block of the circuit diagrams and processflowcharts, and combinations of blocks in the circuit diagrams andprocess flowcharts, can be implemented by special purpose hardware-basedcomputer systems that perform the specified functions or steps, orcombinations of special purpose hardware and computer instructions.

Adaptive UI

FIG. 1 illustrates an example interface 1 structured in accordance withvarious embodiments of the invention. The depicted interface 1 presentsitems, or groups of items, as represented by dynamic icons 5. In someembodiments, the dynamic icons 5 include an item name 6; however, inother embodiments, the dynamic icons 5 may include some other means(e.g., picture, photo, symbol, QR code, ID number, etc.) to identify theitem represented by the dynamic icon 5, as defined above. In oneexample, a dynamic icon 5 may be shaped to generally resemble the itemit represents or there may be some other feature that indicates the itemrepresented.

In some embodiments, as described in detail herein, the interface 1 isconfigured to present visually biased dynamic icons 5 in order torepresent data associated with the items and/or a profile data or abouthow such information or data changes with time. The visual bias may bepresented as a visual indication, as defined above, and/or in someembodiments, a feature or features of the dynamic icon may be biased. Asexplained in further detail below, in some embodiments, the dynamicicons 5 may visualize any data that is of interest to a user viabiasing. Any feature of the dynamic icon 5 may be used to visualize thedata.

The system may determine a visual bias, to be presented via theinterface 1, which indicates a suggested item to a user, such that thevisual biasing presents one dynamic icon as suggested over a secondarydynamic icon. As shown in FIG. 7, each of the dynamic icons 5 may have acommon shape or other common feature, and in some embodiments the visualbias may change the common feature or attribute to indicate a suggesteddynamic icon. For example, in some embodiments, two dynamic icons 5 mayboth have the same shape (e.g., circles). In some embodiments, thesystem may visually bias one of or both of the dynamic icons by changingthe common circular feature of the dynamic icons, such as by alteringthe size, color, border, shading, or any other attribute of the commonfeature to indicate a distinction between the two dynamic icons.Likewise, any feature of the dynamic icons 5 may be biased, for example,and without limitation, a size, color, shading, border or any otherfeature of the dynamic icon. Additionally, as described herein, anynumber of the dynamic icons may be biased independently or relative toone another.

Additionally, as discussed in greater detail herein, the system mayconsider any type of information when biasing the dynamic icons. In someembodiments, the visual bias may be determined by transaction data.Transaction data, as described above, may include any item or profiledata about the buying, selling, or offering of the items. For example,in some embodiments, several dynamic icons may be biased based on theirrelative selection rate, usage rate, popularity, or other transactiondata for each item. Some embodiments may visually bias an item based onthe transaction data associated with a particular profile identifier.For example, the interface may present visually biased dynamic iconsthat indicate a suggested item based on the transaction data of aparticular profile representing a consumer.

In some embodiments, the system may determine a visual bias based onenvironmental data. As defined above, environmental data may includeinformation such as a time of day, time of year, weather, season,geographic or hyper-geographic location, or any other data that givescontext to each item and/or item transaction. For example, some itemsmay be more frequently purchased in winter, or on cold days, and theinterface may present visually biased dynamic icons 5 representing thosemore popular items on days with similar weather conditions.

In some embodiments, the system may also determine the visual bias basedon multiple data sources. As discussed herein, in some embodiments, thesystem may consider multiple factors or data sources in determining theoverall bias for a dynamic icon 5. For example, in some embodiments, thesystem may calculate a visual bias based on transaction data for theitems as well as business data (e.g. inventory information, etc.) foreach of the items. Thus, in this example, a more popular, but out ofstock, item may have the visual bias of its dynamic icon altered so thatthe interface suggests another, less popular item that is in stock. Anycombination of the possible data sources disclosed herein may be used inorder to determine a suggested dynamic icon or hierarchy of dynamicicons to present via the interface.

Some embodiments of the present invention, for example as shown in FIG.49, also use a second screen to display a second interface. In somealternative embodiments, a second interface may be presented on a thesame screen as the first interface. In some embodiments, the systemdetermines a visual bias for one or more dynamic icons based on a set ofdata and/or a relevancy score 4935 and present visually dynamic icons4945 via a first interface on a first screen. In some furtherembodiments, as shown in FIG. 49, a second interface may be presented ona second screen 4950, and may be presented to a different user. Thesecond interface may present a different visual bias for the dynamicicons on the second screen than the first interface on the first screen,based on the information that is relevant to the particular user. Insome embodiments, the system may access an item list 4905 and receivetwo or more profile identifiers 4910 representing at least a firstprofile data 4915 and second profile data 4920. The system may thenaccess the first profile data 4915 and the second profile data 4920corresponding to each profile identifier. The system, either in a singledevice or via a networked set of devices, as described herein, maydetermine a relevancy score for the items based on the first profiledata 4925 and may determine a second relevancy score for the items basedon the second profile data 4930. The system may then determine a firstvisual bias for the dynamic icons on the first interface based on thefirst profile data and the first relevancy scores 4935, and maydetermine a second visual bias for the dynamic icons on the secondinterface based on the second profile data and the second relevancyscores 4940. The visual biases for the dynamic icons may be presented onthe respective first interface 4945 and second interface 4950. Althoughsteps 4925 and 4930 recite determining a relevancy score of each item,alternative embodiments may use the profile data, or transaction dataassociated with the profile data as a source of comparison for either orboth of the first profile data and second profile data as describedherein with respect to the transaction data of FIGS. 10a, 10b, 11a , and11 b.

For example, a first screen may be consumer facing and may visually biasthe dynamic icons to show relevancy of each item to the consumer. Inthis embodiment, the second screen may be provider or provider employeefacing and may visually bias the dynamic icons based on business data orother information in order to facilitate the transaction for both theprovider/provider employee and the consumer. The system may utilize anynumber of screens necessary to present the items as biased dynamic iconsin a meaningful way to each user (e.g. provider, consumer, promotion andmarketing service, etc.).

In some embodiments, the system may give different weights to differentsets of data. For example, in some embodiments, the system may prefermore recent data to older data, so more recent transaction data would begiven more weight in the biasing determination than stale transactiondata.

FIG. 7 illustrates an exemplary embodiment of the interface 1 of thepresent invention, wherein the sizes of the dynamic icons 5 are visuallybiased to indicate transaction data of the represented items. Forexample, the coffee dynamic icon 11 and spaghetti dynamic icon 17 of theembodiment shown in FIG. 7 are determined to be more popular based ontransaction data, i.e., more frequently purchased or more frequentlyselected. Thus, the coffee dynamic icon 11 and spaghetti dynamic icon 17are visually biased (i.e., their sizes have been increased) relative tothe other dynamic icons. In contrast, the flank dynamic icon 16 and eggsdynamic icon 25 of the embodiment shown in FIG. 7 are used lessfrequently so their sizes have been reduced. In some embodiment,visually biased dynamic icons (e.g., coffee dynamic icon 11 andspaghetti dynamic icon 17) may be referred to as suggested dynamic iconswhile other dynamic icons (i.e., flank dynamic icon 16, eggs dynamicicon 25, cobb dynamic icon 20) may be referred to as secondary dynamicicons.

In some embodiments, the system visually biases the features of thedynamic icons 5 relative to one another based on a comparison of theirtransaction data. For example, if the spaghetti dynamic icon 17 in theembodiment shown in FIG. 7 is selected more often than the eggs dynamicicon 25 (or if transaction data processed by one or more back-endservers suggest spaghetti is sold more frequently than eggs), thespaghetti dynamic icon 17 may grow relative to the eggs dynamic icon 25and the eggs dynamic icon 25 may shrink relative to the spaghettidynamic icon 17. In some other embodiments, the system may independentlybias the features of the dynamic icons 5 without relating them to eachother.

In some embodiments of visual biasing, the bias of the dynamic icons maybe changed as needed by the system to indicate an item's relativetransaction data (e.g., popularity) and not necessarily to indicate theoverall transaction data (e.g., the absolute popularity) of an item. Forexample, grilled chicken 22 and flank 16 dynamic icons in FIG. 7 maystill be chosen frequently on an absolute or objective basis, but thepancakes 27, granola 29, and spaghetti 17 dynamic icons 5 may beselected (or sold based on transaction data) relatively more often.Thus, in this example, the pancakes 27, granola 29, and spaghetti 17dynamic icons 5 may be sized a bit larger than the grilled chicken 22and flank 16 dynamic icons.

In some embodiments, the dynamic icons 5 and the interface 1 may bescaled to fit the type of display or screen being used. In an exampleembodiment, the dynamic icons 5 may be proportional to one another suchthat as one dynamic icon increases in size the remainder of the dynamicicons decrease in size so that all of the dynamic icons take upapproximately the same amount of display space as before. Additionally,in some embodiments, the dynamic icons 5 may be configured to overlapone another if they grow sufficiently large, or they may be configuredto deflect away from each other so as to avoid overlapping. In someother embodiments, the dynamic icons 5 may be bounded to a certain gridor zone, such that they are not permitted to expand outside of theirdesignated zone. In some embodiments, when a dynamic icon 5 is visuallybiased to grow to a maximum size for its allocated grid or zone, theremainder of the dynamic icons 5 may be shrunk rather than continuing toincrease the size of such visually biased dynamic icon.

As will be detailed below, the visualizations of the dynamic icons 5 maybe biased in any increment or over any time period or set of datadepending on interests of the consumer, provider, and/or promotion andmarketing service and the specific application. In some embodiments, thebiasing may be updated after each selection indication, oralternatively, it may be updated on a transactional or temporal basis.FIG. 7 illustrates the interface 1 of FIG. 1 having visually biaseddynamic icons 5 after an exemplary time period of one month. FIG. 8demonstrates an example interface 1 having visually biased dynamic icons5 after an exemplary time period of two months. FIG. 9 demonstrates anexample interface 1 having visually biased dynamic icons 5 after anexemplary time period of one year.

In the embodiments shown in FIGS. 7-9, the size of each dynamic icon 5is biased relative to the respective transaction data of the dynamicicons and/or based on item transaction data processed by one or moreback-end systems. For example, in these embodiments, the usage rateindicated in the transaction data of wine 13 remained generally constantduring the one month period between FIG. 1 and FIG. 7, however, thetransaction data of wine 13 dropped during the two month period betweenFIG. 1 and FIG. 8, and dropped further during the one year periodbetween FIG. 1 and FIG. 9.

In another example, the usage rate indicated in the transaction data ofcobb 20 (i.e., cobb salad) remained generally constant during the onemonth period between FIG. 1 and FIG. 7, however, the transaction data ofcobb 20 dropped during the two month period between FIG. 1 and FIG. 8,and then increased during the one year period between FIG. 1 and FIG. 9.An interface may present visually biased dynamic icons based on datafrom any time period depending on a preference data (contained withinthe profile data), a predetermined time period, or an automaticallydetermined time period.

With reference to FIG. 10a , a flow diagram of the system described inFIGS. 7-9 is shown. The system may be configured to access the list ofavailable items 1005 to be sold. In some embodiments, the system maythen access the transaction data 1010, or more generally, item data (notshown) which contains transaction data, such as a usage rate, and otherinformation about each item being sold. Based on the transaction data,the system may calculate at least one suggested dynamic icon 1015 basedon the transaction data. The system may then determine a visual bias forthe at least one suggested dynamic icon relative to a secondary iconthat is not suggested 1020. The interface may then present the visuallybiased dynamic icons 1025.

In some embodiments, the system may receive a selection indication froma user, via the interface, and update one or more databases with theselection information. For example, in the embodiment shown in FIG. 11a, the system may access the item list 1105, may access the transactiondata associated with the items 1110, may determine at least onesuggested dynamic icon based on the transaction data 1115, may determinea visual bias for the at least one suggested dynamic icon relative to atleast one secondary icon 1120, and presents the visually biased dynamicicons 1125. Once the icons are presented via the interface, the systemmay receive one or more selection indications 1130 from the user of oneor more dynamic icons. As discussed in greater detail herein, the systemmay then update the biasing of the dynamic icons based on the selectionindication 1135, and may update one or more LUI databases with theselection information 1140.

While the embodiments of FIGS. 7-9, 10 a, and 11 a depict a visual biasbased on transaction data, one of ordinary skill in the art willappreciate that a more complex system, such as a relevance system, maybe used. For example, as shown in FIG. 10b , the system may access anitem list 1030, and may access the LUI database 1035 to obtain itemand/or profile data. Based on the data in the LUI database, the systemmay determine a relevancy score of each item 1040 using the relevancesystems and processes described herein. The system may then determine avisual bias for the dynamic icons based on the relevancy scores 1045 andmay present the visually biased dynamic icons 1050.

As detailed in FIG. 11a with respect to the system of FIG. 10a , thesystem of FIG. 10b may be configured to receive a selection indicationfrom a user and update a visual bias and/or the database(s) with theselection indication as shown in FIG. 11b . As with FIG. 10b , thesystem may access an item list 1145, may access a LUI database 1150 toobtain item and/or profile data. The system of FIG. 11b may thendetermine relevancy scores for each item 1155 and may determine a visualbias for one or more dynamic icons based on the relevancy scores 1160.One of ordinary skill in the art will appreciate that the system maydetermine relevancy scores of a subset of the total number of itemsdepending on the information being presented and the visible dynamicicons about which information is desired. The system may then presentthe visually biased dynamic icons 1165 and may receive a selectionindication of one or more of the dynamic icons 1170. As discussed ingreater detail herein, the system may then update the biasing of thedynamic icons based on the selection indication 1175, and may update oneor more LUI databases with the selection information 1180.

While one result of the present invention is the visualization of itemor profile data, one of ordinary skill in the art will appreciate thatthe present invention may also be used to increase user efficiency. Forexample, in the embodiments shown in FIGS. 7-9, biasing the features ofeach of the dynamic icons 5 based on the transaction data (oradditionally or alternatively item or profile data) of items that arerepresented by the dynamic icons allows designated or suggested dynamicicons (e.g., the more frequently used as indicated by transaction data)to be more visible and, therefore, easier to access. This allows theuser to spend less time searching for and targeting a desired dynamicicon 5 and speeds up the dynamic icon selection process. Biasing thesize or any other feature of the dynamic icons 5 based on their relativeitem data also allows a user to quickly identify the suggested dynamicicons and may provide a visual recommendation to the user, which mayspeed the item selection process.

The interface 1 may be configured in any layout that suits the needs ofthe user. An alternative interface 101 embodiment is shown in FIG. 12.The layout of the embodiment shown in FIG. 12 includes a number ofcategories 35 with a set of dynamic icons 33 listed under each categoryand an arrow indicator 37 pointing to the currently selected category.In some further embodiments, the size of each category 35 may be biasedbased on that category's transaction data, which may be determined bythe transaction data involving the category itself or transaction datacorresponding to the dynamic icons 5 within each category 35, and/orbased on transaction data (e.g., sales data, redemption data, inventorydata, etc.) processed by a back-end system (e.g., promotion and marketsystem 204, 3^(rd) party system 218, and/or provider system 216 of FIG.2) associated with items represented by the categories and dynamicicons.

In some embodiments, the position of the dynamic icons 33 may be biasedby moving the location of the suggested and secondary dynamic iconswithin the interface based on the item or profile data. For example, insome embodiments, the large dynamic icon 38 (i.e., an example suggesteddynamic icon) may generally be positioned proximate the center of thedisplay (i.e., an area of the display that is deemed of highest priorityor accessibility to a user based on the device being used) whereas thesmaller dynamic icons 39 (i.e., example secondary dynamic icons) may bepositioned proximate the outside of the display (i.e., areas that aredeemed of lower priority or user accessibility).

In some embodiments, positioning one or more dynamic icons 33 based onunderlying suggestions (e.g. determined by item or profile data) mayincrease the efficiency of the user by making certain suggested dynamicicons more accessible. Placing the suggested or more likely to beselected dynamic icons closer together on the interface may also reduceclick time between dynamic icon selections. Additionally, in someembodiments, the position of the dynamic icons 5, 33 may be based on thesimilarity of the items (e.g., similarity of their item data, such ascharacteristic information) or their relevant characteristics to betterorganize the interface. In some embodiments, the groupings of thedynamic icons 5, 33 may be dependent on the characteristics of the itemsrepresented that do not necessarily include usage.

In some embodiments, the positioning of the dynamic icons 5, 33 mayfurther take into account the type of input devices used and thepreference data of the profile. For example, in some embodiments, morecommonly used dynamic icons may be placed closer to the left side of theinterface to allow a left-handed user (e.g., as determined based on auser profile stored to a user database of a provider or a promotion andmarketing service) to reach them more easily. Alternatively, in someembodiments, the user may be holding a portable device, which isrendering the interface on its display, and may only have one handavailable for selecting the dynamic icons. In this regard, the interfacemay be configured to make the dynamic icons easier to reach by movingthem closer to the free hand. In some embodiments, the user may need tostabilize a portable, handheld device when selecting the dynamic iconsand the interface may be configured to place the more commonly useddynamic icons closer to the user's support hand to minimize deflectionof the device. One of ordinary skill in the art will appreciate thatnumerous other configurations of the dynamic icons 5, 33 may becontemplated in accordance with various inventive concepts of thepresent invention.

Multiple Layering

In some embodiments of the invention, as shown in FIGS. 12-16, theinterface may present multiple layers of options for the dynamic iconsrepresenting the various items. With reference to FIG. 12, someembodiments may present a layer of dynamic icons 33 associated with(e.g., beneath or between) the categories 35 when a category isselected. With reference to FIG. 13, an example embodiment of one suchlayer 45 is shown with reference to the coffee dynamic icon 111. In someembodiments, such as the previous embodiments of FIGS. 7-9, when thecoffee dynamic icon 11 is selected, a submenu 45 (shown in FIG. 13) ofadditional options 46, 47, 48, 49 are presented to the user. In thedepicted embodiment, the sublayer/submenu 45 includes additional items(e.g., shots, almond milk, cream, whiskey, etc.) that are commonlyassociated (based on underlying transaction data) with coffeetransactions.

In some embodiments, only a portion of the dynamic icons 5 may have asublayer 45. Some embodiments may present a check dynamic icon 40 toallow the user to close the sublayer 45 once the desired options 46, 47,48, 49 have been selected.

In some embodiments, only items that require additional choices willpresent a sublayer 45 to the user. In the embodiment of FIG. 13, thesublayer option dynamic icons 46, 47, 48, 49 are square shaped. However,one of ordinary skill in the art will appreciate that the dynamic icons46, 47, 48, 49 may have any type of features (e.g., any shape, size,name, color scheme, etc.).

In some embodiments, such as the embodiments shown in FIGS. 13-15,sublayer options 46, 47, 48, 49 may be visually biased relative to theirrespective item or profile data (e.g., a usage rate in the transactiondata) associated with the underlying items. For example, in theembodiment shown in FIG. 14, the dynamic icon 46 representing a shot hasbeen selected and is indicated in the column 42 to the left beneath thecoffee dynamic icon 111. Once the shot dynamic icon 46 is selected, theuser interface increases the size (i.e., an example form of visualbiasing) of the shot dynamic icon 46 so as to indicate an incrementalincrease of representative transaction data as compared to the otherthree dynamic icons 47, 48, 49 that were not selected. In anotherexample, the shot dynamic icon 46 may be similarly increased in sizebased on a back-end system receiving updated transaction data reflectingincreased shot related transactions that are not necessarily related tothe user viewing the interface shown in FIG. 13.

With reference to FIG. 15, in some embodiments, when a second dynamicicon 49 is chosen, the second dynamic icon is also visually biased(e.g., increased in size). As was described above with respect to thedynamic icons 5 of FIGS. 7-9, the dynamic icons 46, 47, 48, 49 of someembodiments of the sublayer 45 may change relative to one another orindependently based on clicks or selections of the dynamic icons 46, 47,48, 49 or based on changes in underlying transaction data. In theembodiment shown in FIG. 15, the whisky dynamic icon 49 has expandedinto the space of the cream dynamic icon 48 but not into the spaces ofthe shot dynamic icon 46 and the almond milk dynamic icon 47. Thisvisual change may suggest, based on dynamic icon selection data and/orunderlying transaction data, that increased whisky interest orassociated transactions tend to come at the expense of cream but not atthe expense of shots or almond milk. Likewise, in the embodiment shownin FIG. 15, the shot dynamic icon 46 has expanded into the space of thealmond milk dynamic icon 47, but not into the spaces of the creamdynamic icon 48 or the whisky dynamic icon 49. This visual change maysuggest, based on dynamic icon selection data and/or underlyingtransaction data, that increased shot interest or associatedtransactions tend to come at the expense of almond milk but not at theexpense of cream or whisky.

Any combination of relative sizing or other alterations to the featuresof the dynamic icons may be utilized as part of the visual biasing toconvey the desired information to the user. For example, in someembodiments, the shot dynamic icon 46 and almond milk dynamic icon 47may expand downward in the depicted display. Likewise, in someembodiments, the cream dynamic icon 48 and whisky dynamic icon 49 mayexpand upward in the depicted display. In FIGS. 13-15, a total outersize is maintained for the four sublayer options 46, 47, 48, 49,however, in some embodiments, the dynamic icons may also expand outward.A person of ordinary skill in the art would appreciate numerous otherembodiments of the relative sizing of the depicted dynamic icons. Asdiscussed above, in some embodiments, the visual biasing (e.g. relativesizing) of the dynamic icons 46, 47, 48, 49 may change based on dynamicicon selections and/or underlying transaction data taken over someperiod of time (e.g., at a refresh rate, by the hour, by the day, by themonth, by the year, etc.).

FIG. 16 shows an alternative embodiment of a sublayer 245 where theavailable modifiers or dynamic icons 246, 247, 248, 249 take up thecenter of the display without rendering the selected dynamic icon orcategory (i.e., the coffee dynamic icon shown in FIGS. 13-15), theassociated column 42, or check dynamic icon 40 being shown. As will beappreciated by one of ordinary skill in the art in view of thisdisclosure, the depicted interface embodiment may be particularly suitedto mobile or tablet device displays where less display space isavailable.

In the embodiment shown in FIG. 17, for example, the interface maypresent a sublayer of options after receiving the selection indication.The system may be configured to access the item list 1705, calculate orreceive a relevancy score for each item 1710, determine a visual biasfor one or more dynamic icons 1715, which may be based on the relevancyscores, and present the visually biased dynamic icons 1720 representingeach item. The system may then receive a selection indication 1725 froma user of a present selection of at least one of the dynamic icons.Based on the selection indication, the system may present a submenulayer of options 1730 related to the selected dynamic icon. In someembodiments, the sublayer's icons may also be visually biased based ontheir relevancy. Although step 1710 recites determining a relevancyscore of each item, alternative embodiments may use one or more sets ofdata as a simpler and/or alternative source of comparison, including butnot limited to transaction data, item data, profile data, etc. asdescribed herein with respect to FIGS. 10a, 10b, 11a , and 11 b.

With reference to FIG. 18, in some embodiments, the system may alsotrack a bill total or “transaction item listing” in an informationcolumn 2. In other embodiments, the transaction item listing mayrepresent a running shopping cart total or similar transactionitemization. In the depicted embodiment, the column 2 does not have torepresent a bill total but may be any list of the items that may be ofinterest to the user. For example, the column 2 in the embodiment shownin FIG. 18 details the items presently selected during the present usertransaction. The embodiment of FIG. 18 lists a coffee 55 along with theprice of the item as having been chosen in the current transaction. Insome embodiments, the data presented by visually biasing the dynamicicons 5 may represent transaction data taken over the long term, e.g.,over multiple transactions taken over an extended period of time, whilethe items listed in column 2 may represent only the currentlycontemplated transaction.

In some embodiments, column 2 may be positioned anywhere withininterface 1 that a user desires and may show any longer or shorter termdata that is desired by the user. In some embodiments, column 2 may alsobe used to depict more detailed information associated with each itemrepresented by the dynamic icons 5 or different types of item andprofile data, such as business data (e.g. inventory data or goals)associated with transaction data concerning the items represented by thedynamic icons 5. In some embodiments, column 2 may also include a totalprice for the presently contemplated transaction and may include a“Charge” dynamic icon 3 or the like to allow the user to complete thetransaction. In some embodiments, as shown in FIG. 18, the column 2 maylist items in text form, but other visual representations of thetransaction, such as the various features of the dynamic icons 5described above, are also envisioned by the present invention.

For example, in the embodiment shown in FIG. 19, the system may accessan item list 1905, determine a relevancy score for each of the items1910, determine a visual bias for one or more of the dynamic icons 1915,and present visually biased dynamic icons 1920, which may represent therelevancy score of each item. In some embodiments, the system may thenreceive a selection indication of one or more of the dynamic icons 1925.Based on the selection indication, the interface may then update thetransaction item listing 1930 (shown as column 2 in FIG. 18) as well asupdating the biasing information 1935 and other LUI databases based onthe selection indication. Although step 1910 recites determining arelevancy score of each item, alternative embodiments may use one ormore sets of data as a simpler and/or alternative source of comparison,including but not limited to transaction data, item data, profile data,etc. as described herein with respect to FIGS. 10a, 10b, 11a , and 11 b.

Predictive Sequencing

With reference to FIG. 20, some embodiments of the present invention mayvisually bias one or more dynamic icons to indicate items that arefrequently chosen together by predictive sequencing. For example, in theembodiment illustrated in FIG. 11, when the caesar (e.g., ceasar salad)dynamic icon 19 is selected, the bill total in column 2 indicates that acaesar salad was selected and the two dynamic icons for panini 23 andsoup 24 are visually biased via shading under the respective dynamicicons. In some embodiments, the predictive sequencing is determinedbased on a relevancy score and/or transaction data of each item to theselected item. In some embodiments, the shading 65, or other visualbiasing, indicates that the panini dynamic icon 23 and soup 24 dynamicicon are frequently chosen after the caesar dynamic icon 19 in thetransaction data and/or that underlying transaction data suggests thatpaninis and soup are commonly purchased with ceasar salads in the sametransactions.

In some embodiments, the shading 65 is configured so as to not obstructthe interactive flow of the device and the interface while yetindicating to the user, in an intuitive fashion, dynamic icons 5 thatare frequently selected and/or items that are frequently purchased inconjunction with or in sequence with a currently selected item asrepresented by the transaction data. While the embodiment shown in FIG.20 depicts shading 65 as an indicator of item association, the interfacemay use any visual biasing, permanent or temporary, such as a visualindication or changing a feature or common feature of one or moredynamic icons as detailed above in order to attract the user'sattention.

Once the predictive sequencing has been presented by visually biasingone or more dynamic icons and a subsequent icon chosen, some embodimentsof the interface 1 may present the dynamic icons 5 in their originalstate (e.g., non-shaded) as shown in FIG. 21. In the depictedembodiment, the soup dynamic icon 24 is selected after the caesardynamic icon 19 and both items 60, 70 are listed in the bill totalcolumn 2. Some embodiments then remove the shading 65 or other visualbiasing (shown in FIG. 20 but not in FIG. 21) from beneath the paninidynamic icon 23 and the soup dynamic icon 24, because the predictivesequence visualization has terminated or been deemed no longer ofinterest. In some embodiments, if a predicted item 23, 24 is not chosenimmediately after a triggering item 19, the shading 65 or emphasisassociated with such predicted items disappears. In other embodiments,the shading 65 or other visual biasing may remain for the duration ofthe transaction. In some embodiments, the duration of the predictivesequence may be user selectable, selectable by the provider or thepromotion and marketing service, or programmatically determined for theinterface 1 based on item and/or profile data.

An example flow diagram of the predictive sequencing is shown in FIG.22. With reference to FIGS. 22-23, the system may be configured toaccess an item list 2205, 2305, determine a relevancy score for theitems 2210, 2310, determine a visual bias for one or more of the dynamicicons based on the relevancy scores 2215, 2315 and present the visuallybiased dynamic icons 2220, 2320. The system may then receive a selectionindication of a dynamic icon from the user 2225, 2325, and based on theselected icon (and the item represented by the icon) suggest one or moreitems via predictive sequencing 2230, 2330. In some embodiments, thesuggested items are chosen by determining a relevancy of each item tothe selected item 2230, 2330. The user may then select the suggesteditem(s) 2235, 2335 or another, non-suggested item 2240, 2340 in thesystem. With reference to FIG. 23, in some embodiments, when the userselects the dynamic icon representing one of the suggested items 2335,the predictive sequencing may be updated 2345 to present another item inthe sequence. Alternatively, in some embodiments, if the user selects anon-suggested dynamic icon representing a non-suggested item 2340, thepredictive sequence may terminate 2350. Although step 2210 of FIG. 22and step 2310 of FIG. 23 recite determining a relevancy score of eachitem, alternative embodiments may use one or more sets of data as asimpler and/or alternative source of comparison, including but notlimited to transaction data, item data, profile data, etc. as describedherein with respect to FIGS. 10a, 10b, 11a , and 11 b.

In some embodiments, an example system may be configured to present apredictive sequencing of items without a user first selecting a dynamicicon 5. For example, in some embodiments, a user may request pairingsuggestions via an input/output module (e.g., touch display, keyboard,etc.) as described below, or the system may automatically displayrelevant pairings or sequences. For example, if the caesar dynamic icon19 and the soup dynamic icon 24 are frequently chosen together (or theunderlying items are generally purchased together based on transactiondata), the interface 1 may indicate their relatedness by presentingtheir features to be similarly biased. For example, the dynamic iconsmay be presented with similar visual biasing or may be biased in closeproximity to one another within the interface 1.

The frequency of selection in the transaction data that is required totrigger the predictive sequencing between two dynamic icons 5 can be anythreshold or percentage of dynamic icon selections. In some embodiments,the predictive sequencing considers how many times two or more dynamicicons have been selected in the same transaction and/or how many timestwo or more underlying items have been redeemed or purchased togetherbased on transaction data. In other embodiments, the system or devicemay consider the number of times one dynamic icon (for example, the soupdynamic icon 24) is selected immediately after another dynamic icon (forexample, the caesar dynamic icon 19) to generate the sequencing.

In some embodiments, two or more dynamic icons may be suggested togethervia predictive sequencing after they have been chosen together apredetermined number of times and/or after their underlying items havebeen purchased or redeemed together a predetermined number of timesbased on underlying item transaction data.

In some embodiments, a predetermined threshold may be based on apercentage. For example, in some embodiments, any dynamic icon 5 that ischosen 10% or more times after another dynamic icon 5 will generate apredictive sequence. Likewise, any item that is purchased or redeemedwith another item in at least 10% of corresponding transactions may alsogenerate a predictive sequence.

In another embodiment, a dynamic icon that is chosen with a seconddynamic icon a certain percentage (e.g., 15%) more than any otherdynamic icon may be recommended via predictive sequencing. Similarly, anitem that is purchased or redeemed with another item a certainpercentage more often may produce a predictive sequencing. In someembodiments, a dynamic icon 5 that is chosen more frequently with asecond dynamic icon 5 than any other pairing with that second dynamicicon 5 may be recommended. In addition, in some embodiments, and asshown in FIGS. 20-21, multiple dynamic icons 23, 24 may be recommendedin connection with a single dynamic icon 5 (for example, the caesardynamic icon 19) or multiple other dynamic icons 5. A person of ordinaryskill in the art may appreciate that any distinguishing relationshipbetween two dynamic icons, or underlying item transaction data, maytrigger the predictive sequencing, and that the relative selection ratesmay be obtained from transaction data taken from a remote device and notnecessarily a specific interface.

With reference to FIG. 24, some embodiments of the present invention maygive a more detailed predictive sequencing. For example, the depictedembodiment uses the categories 35 and the individual dynamic icons 33within each category to illustrate relative selection frequency withinthe predictive sequencing based on the transaction data. In the depictedembodiment, dynamic icons associated with each of the three categories75, 77, 79 are presented proximate different and alternating backgroundcolors.

In some embodiments, when a first category 75 is selected, the interface101 may be configured to present the second 77, third 79, and forth 81most commonly chosen dynamic icons after that category 75 is chosen. Forexample, in some embodiments, the third category 79 is frequently chosenafter the first category 75 but typically not as often as the seconddynamic icon 77. The fourth category 81 is chosen with the firstcategory 75, but not as often as the other two 77, 79. In this way, theinterface 101 may be configured to indicate the relative frequencies ofwith which each option (e.g., dynamic icon) is selected relative to afirst selected dynamic icon by an intuitive visual representation. Inthe depicted embodiment, the frequency of dynamic icon selection isindicated by biasing the dynamic icon size (e.g., dynamic icon 77 islarger than dynamic icons 79, 81) and dynamic icon shading (e.g.,dynamic icon 77 is darker than dynamic icons 79, 81); however, any otherfeature may be biased as will be apparent to one of ordinary skill inthe art in view of this disclosure.

In an alternative embodiment, multiple subsequent steps of thesequential pattern may be shown by differences in visualization of thefeatures of the respective dynamic icons 33 based on the differences inthe transaction data for the respective items. For example, in theembodiment shown in FIG. 24, the second dynamic icon 77 may be pickedmost frequently after the first category 75 and is presented as thedarkest shade. In some further embodiments, the item typically selectedafter the second dynamic icon 77 is presented as the next darkest shade,such as the third category 79 in FIG. 24. And in some furtherembodiments, the item most commonly selected after the third category 79is presented as the next darkest shade, such as the fourth category 81in FIG. 24. Thus, in some embodiments, the first dynamic icon 75 may bechosen by the user and, subsequently, the interface 101 may beconfigured to generate a suggested list of the next three sequentiallychosen options 77, 79 and 81 may be further configured to suggestvisually that the user then pick the second dynamic icon 77, followed bythe third dynamic icon 79, and then followed by the fourth dynamic icon81. As discussed above, with reference to FIG. 23, the system mayterminate the predictive sequencing 2350 if one of the suggested itemsis not chosen.

The system may be configured to suggest multiple subsequent stepsflowing from each dynamic icon selection based on a dynamic iconselection pattern, based on the transaction data, typically chosen foreach item by sequentially visually biasing the dynamic icons. In someembodiments, the dynamic icon selection patterns suggested by the systemmay be relative to the first item selected, meaning the subsequent threeitems 77, 79, 81 are the most common sequence of three chosen after thefirst item. In other embodiments, the presented sequence may begenerated pairwise as the most commonly selected item after eachpreceding item in the sequence, meaning the second dynamic icon 77 isfrequently associated with the first dynamic icon 75, the third dynamicicon 79 is frequently associated with the second dynamic icon 77, andthe fourth dynamic icon 81 is frequently associated with the thirddynamic icon 79. In this last embodiment, there need not be anyrelationship or frequency between the first dynamic icon 75 selectionand the fourth dynamic icon 81 selection so long as the intermediateitems in the sequence connect them.

While the above dynamic icon selection sequences and correlations arebased on dynamic icon selection patterns for illustration purposes, oneof ordinary skill in the art will readily appreciate that such sequencesmay be similarly based, alone or in combination with item data orprofile data patterns. In addition, one of ordinary skill in the artwill appreciate that visually biasing any number or combination offeatures or visual indications of dynamic icons may be used to indicatethe predictive sequencing.

Data Filtering

With reference to FIG. 25, some embodiments of the present invention maypresent a control panel 80 that provides options for the user toconfigure the interface 1. In some embodiments, the user may open andclose the control panel 80 by verbal command, gesture, tactile dynamicicon, on-screen dynamic icon (e.g., soft key), or other types of inputindications that may be facilitate by an input/output module.

In one embodiment, the interface 1 may be configured with an “Ask Lui”dynamic icon 41 (shown in FIG. 12) that, when selected by the user,causes the interface to present the control panel. In the depictedembodiment, the control panel 80 is configured with a “Thanks, Lui” or“Thx, Lui” dynamic icon 43 that is adapted to close the control panel.

In some embodiments, the system may be configured to filter the datapresented by the dynamic icons 5 to suit the needs of the user, and thecontrol panel 80 may be configured to present the user with specificoptions to narrow or alter the data that the interface is configured tovisually represent. In some embodiments, the filtering process may biasthe dynamic icons based on a user request and/or the relevancyinformation relating to that user request, as explained in furtherdetail below. Some embodiments of the present invention mayautomatically filter the data based on previous selections by the useror based on calculated factors that are most relevant to a given user.

In some embodiments, with reference to FIG. 25, the size of the dynamicicons, or other visual biasing of the dynamic icons presented by theinterface may represent total sales data 89 (e.g., all time) associatedwith an item based on the item data. However, with reference to FIG. 26,some embodiments of the present invention may allow the user to filterthe represented data (here, sales data 89) based on a specified timeperiod or other criteria. For example, FIG. 26 represents a selection bythe user of a “this week” 85 filter within the control panel 80. Thesystem has been thus configured to adjust the sizing of various dynamicicons based on a subset of sales data for the given week rather than theprior sizing, which was based on all time sales data. While re-sizing ofthe dynamic icons is shown for illustration purposes, any other featuremodification of the dynamic icons may be used as will be apparent to oneof ordinary skill in the art in view of this disclosure.

As described herein, in some embodiments, the system may visually biasthe dynamic icons based on information other than only the transactiondata. For example, with reference to FIG. 27, the system may bias theplurality of dynamic icons 2720, 2725 representing the items 2705 basedon environmental data 2710, including information such as time period,weather, location, etc. The relevancy score 2715 of the items 2705 maybe determined based on this environmental data. Although step 2715recites determining a relevancy score of each item, alternativeembodiments may use the environmental data or a subset thereof as asource of comparison as described herein with respect to the transactiondata of FIGS. 10a, 10b, 11a , and 11 b.

Likewise, the system may receive a profile identifier 2810 as discussedherein and shown in FIG. 28. The system may then be configured to accessprofile data 2815 associated with the profile identifier. The system maybias 2825 the plurality of dynamic icons 2830 base on the relevancyscore 2820 based on the profile identifier 2810. Although step 2820recites determining a relevancy score of each item, alternativeembodiments may use the profile data, or transaction data associatedwith the profile data as a source of comparison as described herein withrespect to the transaction data of FIGS. 10a, 10b, 11a , and 11 b.

In some embodiments, a user may select between various predeterminedtime period filters (e.g., today, this week, this month, this quarter,all time) that are generated and presented based on the typical usage ofthe program and the desires of the user. In other embodiments, thesystem may be configured to automatically filter the data based on arelevant time period without requiring user input.

In some embodiments, and with reference to FIG. 29, the control panel 80may be configured to allow a user to select the type of data representedby the dynamic icons 5. In the example embodiments shown in FIGS. 25-26,the size or other visual biasings of the dynamic icons 5 represents thenumber of the total sales 89 of each item represented by the respectivedynamic icons for the respective time periods noted in control panel 80.However, the dynamic icon sizes illustrated in the embodiment of FIG. 29reflects the revenue 90 (e.g., revenue to the provider, revenue to thepromotion and marketing service, etc.) generated by each item over adesired time period. In some embodiments, a system may be configured toallow a user to filter the dynamic icon represented data based on timeof day 95, weather 100, or other environmental conditions as discussedherein. Any subset of the item or profile data may be selected from thecontrol panel 80.

With reference to FIG. 30, in response to a user-request to filter thedata 3010, the system may access various item 3015 and profile 3020data. In some embodiments, the system may then determine a relevancyscore 3025 for each item 3005 based on the filtered information,determine a visual bias for one or more of the dynamic icons 3030,and/or present visually biased dynamic icons 3035 representing theinformation desired by the user. Although step 3025 recites determininga relevancy score of each item, alternative embodiments may apply a moresimple filter to one or more sources of data, including but not limitedto the profile data and item data, as a source of comparison asdescribed herein with respect to the transaction data of FIGS. 10a, 10b,11a , and 11 b.

In the embodiments shown in FIGS. 25, 26, and 29, the interface may beconfigured to visually bias the dynamic icons to show other item data orprofile data such as a business data including, for example and withoutlimitation, goal data 105 (e.g., sales goals, impression goals,redemption goals, etc.), inventory data 110, or pairing suggestion 115information. In some embodiments, the goal data is determined by goalidentifications, which may be received from a user, a provider, aconsumer, promotion and marketing service, or any outside source. Insome embodiments, a goal identification is a signal received by thesystem from a provider goal selection, wherein the provider indicates agoal for a particular item. Some embodiments allow a user to visualizegoals 105 through the system that are predetermined or calculatedtargets for each item. As will be described in greater detail herein,the goals of some embodiments may be shown by visually biasing thefeatures of the dynamic icons 5 or by biasing a secondary indicator,such as a ring 147 (shown in FIG. 41). Similarly, in some embodiments,the system may be configured to display inventory 110 informationassociated with each item represented by the respective dynamic icons byeither biasing the features of the dynamic icons or by biasing asecondary indicator, such as a ring 147 (shown in FIG. 41). In someembodiments, the business data may be decremented or incremented basedon a selection indication from a user. For example, upon receiving aselection indication of one of the dynamic icons, the system maydecrement an inventory, goal, or other business data to reflect theselection. The business data may be shown using the standard visualbiasing techniques described herein, or may be presented via a secondaryindicator, as discussed below.

As shown in FIG. 31, in some embodiments, the system may access an itemlist 3105 and proceed with determining relevancy scores for the items3110, determining a visual bias for one or more of the dynamic iconsbased on the relevancy scores 3120, and presenting the biased dynamicicons 3130 while also determining 3115, biasing 3125, and presenting3135 the business data for the items. As discussed in further detailherein, the system may simultaneously and independently display both therelevancy information and the business data to the user. Although step3110 recites determining a relevancy score of each item, alternativeembodiments may use one or more sources of data, including but notlimited to the profile data and item data, as a simpler and/oralternative source of comparison as described herein with respect to thetransaction data of FIGS. 10a, 10b, 11a , and 11 b.

In still other embodiments, the interface may be configured to allow auser to request pairing suggestions 115 via the interface and suchsuggestions may also be shown by a secondary indicator. In someembodiments, the goals 105, inventory 110, and pairing suggestions 115may be shown by independently biasing the size of the dynamic icons anda secondary feature such that the usage of each item (as determinedthrough dynamic icon selections and/or underlying transaction data) andthe desired secondary data are both shown simultaneously.

FIG. 32 represents an alternative embodiment of an example control panel82. In the embodiment of FIG. 32, the user may be able to filter thedata based on item data, (e.g. business or environmental data, such asgoals 106, weather 107, location 120, or time of day 125). In someembodiments, the features of the dynamic icon 33 may also be selectableto reflect a transaction data, such as the number of customers 130 whohave bought each item.

Embodiments of the present invention may be applied to any increment orcategorization of environmental data (e.g., particularly those which mayaffect transactions or other business goals associated with an item)including, but not limited to, various times of day such as morning,afternoon, evening, or specific hour ranges; various weather conditionssuch as rain, fog, sunshine, snow, various temperatures, and any otherpossible weather; various seasons and times of year; or variousgeographic areas of any size or type.

In some embodiments, various filtering options may be used to select aspecific range of data or to bias all of the data based on its relevanceto the selected filter. In some embodiments, the visualization of thedynamic icons 5, 33 may be biased to represent data from only theselected filter. For example, in some embodiments, when the applyweather dynamic icon 107 is selected, the dynamic icons 33 may representonly selections made during a chosen weather condition.

In some alternative embodiments, the system may be configured to filterthe data by biasing all of the data based on the selected option. In oneexemplary embodiment, with reference to FIG. 32 when the apply weatherdynamic icon 107 is selected, the dynamic icons 33 may give more weightto the weather during the selected weather condition but not completelyignore the usage of the dynamic icons 33 during the other possibleweather conditions.

The system may be configured to give the user the option of variousfilters and ranges in a control panel 80, 82 or the like, or the systemmay be configured to automatically apply a filter based on the relevantapplication and data. Additionally, in some embodiments, the system maybe configured to use current environmental data (e.g., as determined byaccessing environmental data from a mobile device weather application orfrom a remote server) in order to filter the data without requiringspecific direction by a user to do so, or the system may be configuredto allow the user to select a different environmental data (i.e.,different from the one determined for the location of particularinterest), time period, or other limiting data. One of ordinary skill inthe art will appreciate that any item or profile data, such as length oftime period or environmental data may be available as a filtering optionfor the user through the interface based on the user's preference andthe specific application.

Reference will now be made to the embodiments shown in FIGS. 33-37,which show various sets of dynamic icons 5 having different filtersselected. One embodiment, shown in FIG. 33, represents dynamic iconselection and/or transaction data for various items across all timeperiods with no filters applied.

FIG. 34 modifies the illustration of FIG. 33 by configuring the systemto apply a 9:00 a.m. filter. In the depicted embodiment, the dynamicicons 5 of the items most frequently purchased at or around 9:00 a.m.are presented to the user as larger. In this exemplary embodiment, eggs25, brie 26, pancakes 27, french toast 28 and granola 29 (e.g.,breakfast foods) are selected more frequently and/or underlying itemsare purchased more frequently based on transaction data and thus thedynamic icons are displayed larger with the 9:00 am filter applied. Thedynamic icons 5 that are not as frequently selected during the 9:00 a.m.time period in this embodiment, such as flank 16 and duck 15 (e.g.,dinner foods), are displayed as smaller in size.

FIG. 35 illustrates an embodiment of the present invention where a 1:00p.m. filter is selected. In this example the dynamic icons mostfrequently selected or associated with items most frequently purchasedat or around 1:00 p.m., such as soup 24, soda 10, almond 21, and caesar19 are visually biased to be larger while the dynamic icons 5 that arenot as frequently selected or associated with items as frequentlypurchased at or around 1:00 p.m., such as beer 12, wine 13, and tea 14are biased to be smaller.

FIG. 36 illustrates an embodiment of the present invention where theinterface has a 7:00 p.m. filter applied. In this embodiment, the cobb20, spaghetti 17, and soda 10 dynamic icons are more frequently selectedat 7:00 p.m. and are visually biased to be larger, but items such aseggs 25 and brie 26 are less popular at 7:00 pm and, thus, are visuallybiased to be smaller. In some embodiments, the system may be configuredto filter for any predetermined range around the selected time.

FIG. 37 illustrates an embodiment of the present invention where both a7:00 p.m. filter and a rain filter have been applied. For example, inthis embodiment, as compared to FIG. 36, pancakes 27 and french toast 28become illustrated as more frequently selected when it's raining at oraround 7:00 pm than when it is not. This frequency of selectioncorrelation may be based on dynamic icon selection data or underlyingtransaction data as discussed above. In some embodiments, the filtersmay simply combine to show the relative popularity of items at oraround, for example, 7:00 pm at the same time that it is raining. Insome other embodiments, as discussed above, the filters may interactwith the data differently. For example, in one exemplary embodiment, thetemporal data filters may eliminate any transactions not occurring at oraround the specified time, but the environmental filters may bias thedata based on its relatedness to rain. For example, in the previousembodiment, if a 7:00 pm filter is applied, transactions occurring at5:00 am may not be considered, but snow occurring around 7:00 pm will bepresented and the data weighted because of snow's closeness to rain. Aperson of ordinary skill in the art will appreciate numerouscombinations and iterations of the system filters to present the userwith any relevant data by visually biasing the.

FIG. 38 shows an alternative embodiment of the environmental filters.For example, a day time option 140 may be selected and a location option135 may be selected and presented in the upper left corner of theinterface display to indicate which filters are currently active. One ofordinary skill in the art will appreciate that numerous indicators ofthe active filter are feasible and may be envisioned by the presentinvention. In some embodiments, as described in further detail below,the information relevant to a particular user may be filtered viamachine learning.

User-Dependent

As discussed herein, system may be configured to represent datadifferently based on the user. In particular, the system may bias thedynamic icons based on the specific user or type of user and may presentany data relevant to the particular user. The interface may be presentedto any type of user, including a consumer, provider, provider employee,or promotion and marketing service, and may present the informationdesired by and relevant to that user to facilitate a transaction ortransactions.

For example, in one embodiment, a business owner (e.g., a provider) maybe interested in total revenue generated by each item for all time ineach of her stores, so the system may bias, for example, the size of itsdynamic icons as total revenue generated for each item for all time.Alternatively, a business owner or store manager may be interested inwhich items sell best at specific times of day, in order to determinewhat is worth preparing at various times in the day. For example, ifEggs sell best in the morning and are rarely purchased after noon, theinterface may be configured to present the sale of Eggs at various timesin the day and the business owner may decide to stop selling Eggs afterlunch. These questions or preferences may be input into the system anddetermined by a relevancy score calculation for each item.

In another embodiment, the interface may be used by a sales clerk (e.g.,a provider employee) who may be more interested in total sales forsimilar times of day in the last week to determine which inventory tohave on hand during that period or perhaps which items to suggest toconsumers during that period. For example, the system may bias the itemsto show relative item sales within one hour of the current time, so thatwhen a customer arrives at 6:45 pm, the sales clerk may recommend itemsthat are most frequently sold between 5:45 pm and 7:45 pm.Alternatively, a provider or provider employee may wish to know whichitems need to be ordered more or less frequently, so the system may biasthe dynamic icons to display an inventory over a given time period todemonstrate which items are in surplus and which are selling out.

In some embodiments, the interface may be configured to presentinformation for a non-user as a recommendation. For example, in someembodiments, the interface may present a suggested dynamic icon to aprovider employee, where the suggested dynamic icon is a suggestion fora consumer. In this example, the visual bias is determined by a thirdparty consumer's likely preferences and presented to the provideremployee for the purpose of making a recommendation to the consumer.

In another embodiment, the interface may be consumer-facing and may betailored to a consumer's needs. For example, a consumer may be moreinterested in which items they personally have purchased over the lastseveral months and may not care as much what other customers havepurchased. Alternatively, in some embodiments, the system may presentthe most popular items for a consumer's specific demographic. Forexample, if young, female consumers typically purchase Duck, the systemmay bias Duck as a more popular option based if the consumer is a youngfemale.

In another embodiment, the system may be tailored to a promotion andmarketing service. In such an embodiment, the interface may display aseries of providers as the available items, and display various datasets concerning the different providers. For example, the system may usea geographic filter to determine which promotions are most popular in agiven city or region. The system may also display to a promotion andmarketing service which providers generate the most revenue for theservice overall. In some embodiments, the system may be configured toallow each user to select the display options most relevant to orinteresting to them.

In some embodiments, for example, as shown in FIG. 28, a profile ID orprofile identifier 2810 is tracked and received by the system togenerate appropriate filters for display and/or to automatically biasthe dynamic icons based on the relevant information for the particularuser. In some embodiments, the profile identifier 2810 may identify auser, consumer, provider, provider employee, or promotion and marketingservice and may also contain information such as a preference for aparticular type of food, a filtering choice or background informationabout the profile. As discussed above, the profile identifier mayindicate a consumer in order to present a suggested dynamic icon to aprovider employee for the purpose of suggesting the dynamic icon to theconsumer. Generally, the profile identifier may represent any person,entity, or group of people that the system presents information to orfor.

In some embodiments, the profile identifier may be input by a user ormay be received or stored by the system. For example, in someembodiments, a user may be prompted to enter a profile identifier whenusing the interface. In some alternative embodiments, a provideremployee may enter or receive the profile identifier from a consumer,where the profile identifier represents the consumer and the systembiases the dynamic icons to display relevant items to the consumer. Insome embodiments, the profile may be transmitted via a remote device,such as a key fob or cellular phone to the system. In some otherembodiments, the profile identifier and any associated information maybe retrieved by the system from a server or other remote storage medium.In some embodiments, the process of identifying the profile and/orpresenting relevant information may be achieved by heuristic ormachine-learning, as explained in further detail below.

In some embodiments, the system may receive the profile identifier andpresent the profile data on the interface. With reference to FIG. 39,the system may receive a profile identifier and present, via theinterface, a notification 400 of the profile identifier. In someembodiments, the notification 400 may be a photo associated with theprofile, such as a consumer photo. The system may be designed to presentthe profile identifier identification to the profile-holder or to athird party, such as a provider employee. After receiving the profileidentifier, the system may visually bias the dynamic icons to present arecommendation 405 based on the profile identifier and any profile dataassociated with the profile. In some embodiments, the profile identifierand/or profile data may cause the system to bias a feature of thedynamic icons that are suggested for the consumer or other profileidentifier. For example, in the embodiment shown in FIG. 39, the systemindicates that Eggs 25, Brie 26, and Garden Salad 18 are recommended byadding shading 405 around the icons.

In some further embodiments, the system may give a user the option ofopening a submenu 410 containing relevant information for the profileidentifier based on the profile data. For example, with reference toFIG. 40, the submenu 410 may present historical profile data includinginsights 425 such as allergy information and a summary of their visitsto the provider. The submenu 410 may also show a transaction data 415associated with the profile data and frequent customer status, alongwith the particular items most frequently purchased 430 by a consumerand any profile-specific promotions 420. This information may bepresented either to the profile holder or to a third party. If presentedto a consumer, the submenu 410 may allow the consumer to take advantageof any promotions 420 and may help the consumer make a quick decisionwhen ordering. If presented to a third party, such as a provideremployee, the submenu 410 may allow the employee to make recommendationsto the profile holder and offer promotions that the profile holder maybe interested in.

In any of the embodiments discussed above, multiple displays orinterfaces may be presented to different users to facilitate atransaction. For example, a provider may use multiple interfaces for aconsumer and a provider employee to display relevant information to eachparty individually. In particular, the consumer may be presented withthe most popular items at the present time and location, while theprovider employee is simultaneously shown the current inventory for eachitem in a separate interface in order to recommend a well-stocked itemor generate a request for additional supplies. Alternatively oradditionally, a provider may have an additional interface that trackstotal revenue from each item while the provider employee and theconsumer continue the transaction. For example, with reference to FIG.31, the plurality of items may be visually biased based on theirrelevancy scores 3120 on one interface and may be visually biasedrelative to the business data 3125 simultaneously on another interface.One of ordinary skill in the art will appreciate the numerouscombinations of interfaces and users that can be utilized to generatethe most relevant information possible in order to facilitate atransaction. In some embodiments, as described in further detail below,the most relevant information to a particular user of the system may bedetermined via machine learning.

Machine Learning

Machine learning is often used to develop a particular patternrecognition algorithm (i.e., an algorithm that represents a particularpattern recognition problem, such as relevance in the LUI system) thatis based on statistical inference. In some embodiments, the systemreceives large quantities of signals from a variety of sources and mustdetermine the relevance of the signals to a particular user, aparticular filter, or a particular subset of transaction information.

For example, a set of clusters may be developed using unsupervisedlearning, in which the number and respective sizes of the clusters isbased on calculations of similarity of features of the patterns within apreviously collected training set of patterns. In another example, aclassifier representing a particular categorization problem may bedeveloped using supervised learning based on using a training set ofpatterns and their respective known categorizations. Each trainingpattern is input to the classifier, and the difference between theoutput categorization generated by the classifier and the knowncategorization is used to adjust the classifier coefficients to moreaccurately represent the problem. A classifier that is developed usingsupervised learning also is known as a trainable classifier.

In some embodiments, content analysis includes a source-specificclassifier that takes a source-specific representation of the contentreceived from a particular source as an input and produces an outputthat categorizes that input as being likely to include a relevant datareference or as being unlikely to include a relevant data reference. Insome embodiments, the source-specific classifier is a trainableclassifier that can be optimized as more instances of content foranalysis are received from a particular source.

In embodiments, analysis ends if the system determines that receivedcontent does not include at least one relevant data reference.

In embodiments, the system determines whether a referenced relevant datais already known to the system. In some embodiments, this determinationis based on whether data representing the referenced relevant data isstored is a data repository. In embodiments, analysis ends if the systemdetermines that a referenced relevant data already is known to thesystem.

If the system determines that a previously unknown relevant data isreferenced within the content data, the system determines whether thecontent data quality needs verification. In some embodiments, thedetermination of whether particular content data quality needsverification is based in part on a confidence rating associated with thesource that provided the content (e.g., received directly by the system,by a connected or related system, or from a secondary source). There area variety of data quality signals upon which, alone or in combination, asource confidence rating may be based. For example, in some embodiments,the content provided by a server that specializes in notifications ofrelevant user data and that previously has published content thatprovided references to several sets of relevant data may not needfurther verification. In embodiments, if the system determines that thedata quality of the received content does not need verification, datarepresenting the referenced relevant data is stored in the datarepository.

In embodiments, if the system determines that the data quality of thereceived content does need verification (e.g., untrustworthy data froman outside source), the system submits data representing the referencedrelevant data for verification. Verification of a relevant data may be amanual process, an automatic process, or a combination. Verification ofdata quality may be based in part on attributes of the data (e.g., arethe results similar to the subset of data collected by the system?),and/or on attributes of the received content (e.g. does the dateindicate that this reference is stale?). In some embodiments, the systemcollects references to previously unknown data that were extracted fromcontent received during a predetermined time period, (e.g., a week) andthen submits the set of collected references for verification.Additionally or alternatively, in some embodiments, the system submits arelevant data reference for verification directly after identifying thereference within received content.

In embodiments, if the system determines that a reference to apreviously unknown relevant data is verified, data representing thereferenced relevant data is stored in the data repository.

In embodiments, a confidence rating is associated with each source thathas provided content referencing a previously unknown relevant data. Inembodiments, the system updates the confidence rating associated withthe source that provided the reference to the relevant data based inpart on the content data quality verification results. For example, inembodiments, the system may increase a confidence rating if the relevantdata reference is verified and, conversely, the system may decrease aconfidence rating if the relevant data reference is not verified. Inanother example, the system may increase a confidence rating if contentreceived from a particular source is determined to include a relativelygreater number of verified relevant data references than contentreceived from other sources within a predetermined time period. In someembodiments in which the source is associated with a source-specificclassifier, the confidence rating is based in part on a percentage ofsuccessful determinations that content includes a relevant datareference. The process ends after the system updates the confidencerating.

Signals

The system may consider at least one or more of the following signalsthat may be weighted, filtered, or used in connection with variousheuristic or machine learning algorithms discussed in greater detailherein, including:

-   -   a. Dynamic icon clicks, presses, selections, or mouseovers    -   b. Category clicks, presses, selections, or mouseovers    -   c. Item clicks, presses, selections, or mouseovers    -   d. Popularity, as indicated by usage rate, selection rate,        sell-out rate, or any other indication of an item's desirability    -   e. Item data, including:        -   i. transaction data        -   ii. business data        -   iii. environmental data        -   iv. characteristic information    -   f. Transaction data, including:        -   i. sales data, such as past and predicted revenue, the            amount of an item sold, profits, or any other sales metric        -   ii. redemption data        -   iii. return data        -   iv. transaction metadata (e.g. data associated with a            transaction including: hyper-geographic location; time of            day; season; weather; consumer identification data including            gender, age, socioeconomic status; item information; or            provider information)    -   g. Profile ID or Profile identifier (e.g. IP address, MAC        address, customer number, merchant number, store number, etc.)    -   h. Profile Data, including:        -   i. transaction data        -   ii. biographical data        -   iii. preference data    -   i. Inventory data    -   j. Other business data, including:        -   i. goals        -   ii. quotas        -   iii. revenue        -   iv. number of customers        -   v. sales    -   k. Environmental signals, including:        -   i. time of day        -   ii. season        -   iii. weather        -   iv. geographic or hyper-geographic location    -   l. Any time periods

Various embodiments of the disclosure herein may reference dynamic iconpresses, clicks, or transactions as signals, however, any of the abovesignals may be used in the LUI system. Each of these signals may be usedin connection with machine learning techniques discussed herein, andthose generally known to one of ordinary skill in the art, to identifypatterns, to rank items, and to determine visual biasing of dynamicicons as discussed herein.

Multiple Indicators

Some embodiments of the present invention have the capability of showingmore than one set of data at the same time as discussed above. In someembodiments multiple features of the dynamic icons 5 may be visuallybiased, independently of one another or relative to one another andmultiple indicators on the dynamic icons may be biased to visualizedifferent sets of data for each item as desired by the user.

With reference to FIG. 41, an example embodiment shows a ring 147 aroundeach dynamic icon 5 that indicates a secondary data about each item. Inthe embodiment shown in FIG. 42, the ring 147 around each item reflectsa goal for the item (e.g., 500 items sold). In this embodiment, once thesecondary ring 147 display is activated or once the goal or other metrichas been reached, the interface 1 is configured to present an indicationof the goal or other metric being reached via subtle visual indication145 or other visual biasing means. In some embodiments, with referenceto FIG. 43, the visual indication 145 may settle or disappear after ashort time of the goal or other metric display being activated or thegoal or other metric being reached. With reference to FIG. 31, thedynamic icons may be visually biased using the rings to display thebusiness data 3135 and may be visually biased separately to display therelevancy information 3130.

FIGS. 41-47 illustrate embodiments of biasing the dynamic icons whereina ring 147 on each dynamic icon 5 represents a goal and the completenessof the ring 147 represents how close the particular dynamic icon 5 is toits respective goal. For example, in the embodiment shown in FIG. 42,the rings 147 around the pancakes 27, french toast 28, and tea 14dynamic icons are complete and full indicating that the goals for thosethree dynamic icons have been reached for a predetermined time period.The goal, in some embodiments, may be set by the user or setautomatically based on previous usage of each dynamic icon 5 from apredetermined time period and/or based on underlying transaction dataassociated with the items represented by the dynamic icons. In somealternative embodiments, the ring 147 may instead count down, meaningeach of the rings 147 may begin as full and incrementally shortensaround its respective dynamic icon 5 until the goal is reached and thering 147 is no longer visible.

FIGS. 43-45 show the garden dynamic icon 18 being selected multipletimes, as indicated by the garden salad 150 appearing in the column 2 tothe left. After each selection, the ring 147 around the garden dynamicicon 18 is biased so as to incrementally fill. In some embodiments, withreference to FIG. 46, when the garden salad reaches its goal, the ring147 fills completely around the garden dynamic icon 18 and the goalbeing reached is indicated to the user by biasing the icon with a visualindication 145. In some embodiments a visual indication 145 or othermeans may be used as an alert to signal to the user that the businessdata (e.g., goal, average sales metric, desired revenue, inventoryrestock point, etc.) has reached a predetermined threshold. Again, insome embodiments, once the goal is reached the visual indication 145 maydissipate after a certain amount of time. FIG. 47 shows the gardendynamic icon 18 after the visual indication 145 has faded and thedynamic icons 5 have returned to an initial state.

Additionally, in some embodiments, the goal or other metric may eitherreset immediately or reset at the end of a predetermined time period(e.g., reset at the end of the day, quarter, or other business cycle)and begin counting again. In some embodiments, the goals or other metricof the ring 147 for each of the dynamic icons 5 may all reset at thesame time, or they may individually reset as they are updated, forexample, in the case of inventory replenishment.

Alternatively, the rings 147, in some embodiments, may show any otheritem or profile data such as an inventory. The inventory display may beindicated by the size of the dynamic icons 5 or may be indicatedsecondarily by the rings 147 while still tracking the usage of thedynamic icons 5 by their size. In this case, the fullness of the ring147 around each dynamic icon 5 may indicate an inventory remaining andthe ring 147 may either fill around the dynamic icon 5 or reduce aroundthe dynamic icon 5 until the inventory is gone. As detailed above, thegoals, inventory, or other data may be presented by the visualization ofthe dynamic icon 5 itself instead of the usage data, and need not use asecondary ring 147. The secondary ring, as with the dynamic icons 5themselves, may be biased to visualize any type of data and any metricdesired by the user.

With reference to FIG. 48 an alternative embodiment of the secondaryindication is shown where the rings 148 are visualized as shading aroundboth the dynamic icons 5 and the categories 35 such that goals,inventory, or any other desired metrics for each item and total goals ormetrics for each category are tracked and indicated.

Many modifications and other embodiments of the inventions set forthherein will come to mind to one skilled in the art to which theseembodiments of the invention pertain having the benefit of the teachingspresented in the foregoing descriptions and the associated drawings.Therefore, it is to be understood that the embodiments of the inventionare not to be limited to the specific embodiments disclosed and thatmodifications and other embodiments are intended to be included withinthe scope of the appended claims. Although specific terms are employedherein, they are used in a generic and descriptive sense only and notfor purposes of limitation.

1. A method of generating a visually biased computer interface on ascreen comprising: presenting, via an interface, a plurality of dynamicicons representing a plurality of items, wherein the plurality ofdynamic icons are configured to be selectable by a user; calculating,via a processor, a relevancy score for each item of the plurality ofitems relative to a first item of the plurality of items, determining asuggested item of the plurality of items based upon a relevancy score ofthe suggested item relative to the first item, wherein the relevancyscore of the suggested item is greater than a threshold relevancy score,determining a visual bias for a suggested dynamic icon of the pluralityof dynamic icons representing the suggested item relative to at leastone secondary dynamic icon of the plurality of dynamic icons; andapplying the visual bias, via the interface, to the suggested dynamicicon.
 2. The method of claim 1, wherein applying the visual bias to thesuggested dynamic icon comprises varying a common feature shared betweenthe suggested dynamic icon and the at least one secondary dynamic icon.3. The method of claim 1, wherein applying the visual bias to thesuggested dynamic icon comprises varying a size of the suggested dynamicicon relative to the at least one secondary dynamic icon.
 4. The methodof claim 1, wherein applying the visual bias to the dynamic iconcomprises varying a color of the suggested dynamic icon relative to theat least one secondary dynamic icon.
 5. The method of claim 1, whereinapplying the visual bias to the suggested dynamic icon comprises varyinga shading of the suggested dynamic icon relative to the at least onesecondary dynamic icon.
 6. The method of claim 1, wherein applying thevisual bias to the suggested dynamic icon comprises varying a border ofthe suggested dynamic icon relative to the at least one secondarydynamic icon.
 7. The method of claim 1, wherein the visual bias istemporary.
 8. The method of claim 7, further comprising removing thevisual bias after a subsequent selection indication.
 9. (canceled) 10.The method of claim 1, wherein the relevancy score for each of theplurality of items is based on environmental data.
 11. The method ofclaim 10, wherein the environmental data comprises at least one of atime of day, time of year, weather, and location.
 12. The method ofclaim 1, wherein a suggested relevancy score for the one suggested itemis greater than a secondary relevancy score for each of at least onesecondary items.
 13. (canceled)
 14. The method of claim 1, furthercomprising: determining a second visual bias for a second suggesteddynamic icon relative to the at least one secondary dynamic icon; andapplying the second visual bias to the second suggested dynamic icon.15. The method of claim 1, wherein determining the suggested itemcomprises: accessing transaction data corresponding to each of theplurality of items, and determining the suggested item based on thetransaction data.
 16. The method of claim 15, wherein determining thesuggested item further comprises: accessing a selection rate for eachitem of the plurality of items, wherein the selection rate comprises arate at which each item of the plurality of items is selected in a sametransaction as the one item, wherein the suggested item is determinedbased on the selection rate for each item of the plurality of items. 17.The method of claim 15, wherein determining the suggested item furthercomprises: accessing a sequential selection rate for each item of theplurality of items, wherein the sequential selection rate comprises arate at which each item of the plurality of items is selected followinga selection of the one item, wherein the suggested item is determinedbased on the sequential selection rate for each item of the plurality ofitems.
 18. The method of claim 15, wherein the suggested item comprisesa first suggested item, the method further comprising: a secondsuggested item, such that a first visual bias is applied to a firstdynamic icon representing the first suggested item and a second visualbias is applied to a second dynamic icon representing the secondsuggested item based on the transaction data for each of the pluralityof items.
 19. An apparatus is provided for generating a visually biasedcomputer interface on a screen, the apparatus comprising at least aprocessor, and a memory associated with the processor having computercoded instructions therein, with the computer instructions configuredto, when executed by the processor, cause the apparatus to: present, viaan interface, a plurality of dynamic icons representing a plurality ofitems, wherein the plurality of dynamic icons are configured to beselectable by a user; calculate a relevancy score for each item of theplurality of items relative to a first item of the plurality of items;determine a suggested item of the plurality of items based upon arelevancy score of the suggested item relative to the first item,wherein the relevancy score of the suggested item is greater than athreshold relevancy score; determine a visual bias for a suggesteddynamic icon of the plurality of dynamic icons representing thesuggested item relative to at least one secondary dynamic icon of theplurality of dynamic icons; and applying the visual bias, via theinterface, to the suggested dynamic icon.
 20. The apparatus of claim 19,wherein applying the visual bias to the suggested dynamic icon comprisesvarying a common feature shared between the suggested dynamic icon andthe at least one secondary dynamic icon.
 21. The apparatus of claim 19,wherein applying the visual bias to the suggested dynamic icon comprisesvarying a size of the suggested dynamic icon relative to the at leastone secondary dynamic icon.
 22. The apparatus of claim 19, whereinapplying the visual bias to the suggested dynamic icon comprises varyinga color of the suggested dynamic icon relative to the at least onesecondary dynamic icon.
 23. The apparatus of claim 19, wherein applyingthe visual bias to the suggested dynamic icon comprises varying ashading of the suggested dynamic icon relative to the at least onesecondary dynamic icon.
 24. The apparatus of claim 19, wherein applyingthe visual bias to the suggested dynamic icon comprises varying a borderof the suggested dynamic icon relative to the at least one secondarydynamic icon.
 25. The apparatus of claim 19, wherein the visual bias istemporary.
 26. The apparatus of claim 25, further configured to removethe visual bias after a subsequent selection indication.
 27. (canceled)28. The apparatus of claim 19, wherein the relevancy score for each ofthe plurality of items is based on environmental data.
 29. The apparatusof claim 28, wherein the environmental data comprises at least one of atime of day, time of year, weather, and location.
 30. The apparatus ofclaim 19, wherein a suggested relevancy score for each of the suggesteditems is greater than a secondary relevancy score for each of at leastone secondary items.
 31. (canceled)
 32. The apparatus of claim 19,further configured to: determine a second visual bias for a secondsuggested dynamic icon relative to the at least one secondary dynamicicon; and apply the second visual bias to the second suggested dynamicicon.
 33. The apparatus of claim 19, wherein determining the suggesteditem comprises: accessing transaction data corresponding to each of theplurality of items, and determining the suggested item based on thetransaction data.
 34. The apparatus of claim 33, wherein determining thesuggested item further comprises: accessing a selection rate for eachitem of the plurality of items, wherein the selection rate comprises arate at which each item of the plurality of items is selected in a sametransaction as the one item, wherein the suggested item is determinedbased on the selection rate for each item of the plurality of items. 35.The apparatus of claim 33, wherein determining the suggested itemfurther comprises: accessing a sequential selection rate for each itemof the plurality of items, wherein the sequential selection ratecomprises a rate at which each item of the plurality of items isselected following a selection of the one item, wherein the suggesteditem is determined based on the sequential selection rate for each itemof the plurality of items.
 36. The apparatus of claim 33, wherein thesuggested item comprises a first suggested item, wherein the computerinstructions further comprise: a second suggested item, such that afirst visual bias is applied to a first dynamic icon representing thefirst suggested item and a second visual bias is applied to a seconddynamic icon representing the second suggested item based on thetransaction data for each of the plurality of items.
 37. A computerprogram product is provided for generating a visually biased computerinterface on a screen, the computer program product comprising anon-transitory computer readable medium having computer programinstructions stored therein, said instructions when executed by aprocessor: presenting, via an interface, a plurality of dynamic iconsrepresenting a plurality of items, wherein the plurality of dynamicicons are configured to be selectable by a user; calculating, via aprocessor, a relevancy score for each item of the plurality of itemsrelative to a first item of the plurality of items, determining asuggested item of the plurality of items based upon a relevancy score ofthe suggested item relative to the first item, wherein the relevancyscore of the suggested item is greater than a threshold relevancy score,determining a visual bias for a suggested dynamic icon of the pluralityof dynamic icons representing the suggested item relative to at leastone secondary dynamic icon of the plurality of dynamic icons; andapplying the visual bias, via the interface, to the suggested dynamicicon. 38.-54. (canceled)
 55. The method of claim 1, wherein determiningthe suggested item occurs in response to receiving a selectionindication of a first dynamic icon associated with the first item of theplurality of items.
 56. The method of claim 55, further comprisingreceiving a second selection indication; and when the second selectionindication is associated with the suggested item, determining a secondsuggested item of the plurality of items based on the selectionindication, determining a second visual bias for a second suggesteddynamic icon relative to the at least one secondary dynamic icon, andapplying the second visual bias to the second suggested dynamic icon;and when the second selection indication is not associated with thesuggested item, removing the visual bias.
 57. The method of claim 1,further comprising receiving a second selection indication; and when thesecond selection indication is associated with the suggested item,determining a second suggested item of the plurality of items based onthe selection indication, determining a second visual bias for a secondsuggested dynamic icon relative to the at least one secondary dynamicicon, and applying the second visual bias to the second suggesteddynamic icon; and when the second selection indication is not associatedwith the suggested item, removing the visual bias.
 58. The method ofclaim 1, further comprising determining a first visual bias for a firstdynamic icon representing the first item relative to the at least onesecondary dynamic icon, and applying the first visual bias to the onedynamic icon simultaneous with applying the visual bias to the suggesteddynamic icon.
 59. The apparatus of claim 19, wherein determining thesuggested item is configured to occur in response to receiving aselection indication of a first dynamic icon associated with the firstitem of the plurality of items.
 60. The apparatus of claim 59, whereinthe apparatus is further configured to receive a second selectionindication; and when the second selection indication is associated withthe suggested item, the apparatus is configured to determine a secondsuggested item of the plurality of items based on the selectionindication, determine a second visual bias for a second suggesteddynamic icon relative to the at least one secondary dynamic icon, andapply the second visual bias to the second suggested dynamic icon; andwhen the second selection indication is not associated with thesuggested item, the apparatus is configured to remove the visual bias.61. The apparatus of claim 19, wherein the apparatus is furtherconfigured to receive a second selection indication; and when the secondselection indication is associated with the suggested item, theapparatus is configured to determine a second suggested item of theplurality of items based on the selection indication, determine a secondvisual bias for a second suggested dynamic icon relative to the at leastone secondary dynamic icon, and apply the second visual bias to thesecond suggested dynamic icon; and when the second selection indicationis not associated with the suggested item, the apparatus is configuredto remove the visual bias.
 62. The apparatus of claim 19, wherein theapparatus is further configured to determine a first visual bias for afirst dynamic icon representing the first item relative to the at leastone secondary dynamic icon, and apply the first visual bias to the onedynamic icon simultaneous with applying the visual bias to the suggesteddynamic icon.